Posts from the ‘Analyst Research: Forrester & IDC’ Category

Nov 10

Top 10 Identity Security Insights from Forrester’s 2025 Security & Risk Summit

Bottom line: Identity security stands at an unprecedented crossroads, with machine identities creating greater complexity and potential chaos every security professional needs to plan for.

At Forrester’s 2025 Security & Risk Summit, Merritt Maxim, VP and Research Director at Forrester, delivered critical insights highlighting the escalating threats shaping identity security’s evolution. CISOs and security leaders find themselves navigating surging threats driven by generative AI, the rapid proliferation of non-human identities, and outdated IAM infrastructures originally designed solely for compliance. Maxim emphasized a pressing urgency: identity strategies must adapt or risk catastrophic breaches and compliance failures.

Here’s a detailed breakdown of the top 10 insights from Forrester’s Summit, including the specific slides from Maxim’s presentation and deeper insights from Forrester’s latest data:

1. Identity Security Budgets Accelerate Toward $27.5B by 2029

IAM investment is growing explosively, set to nearly double from $13.4 billion in 2024 to $27.5 billion by 2029, driven by the escalating complexity and severity of identity-related threats such as AI-driven deepfakes, sophisticated supply-chain attacks, and rampant cloud misconfigurations. This positions IAM as cybersecurity’s third fastest-growing segment, underscoring identity security as a business-critical imperative.

2. Hybrid IAM Still Dominates—77% Keep On-Premise Components

Despite the relentless push to the cloud, 77% of organizations continue relying on hybrid IAM deployments due to legacy infrastructure and regulatory constraints. Fully cloud-based identity management remains a distant reality, with only 9% fully transitioned. Maxim stressed hybrid IAM’s persistence, highlighting the necessity for seamless integration capabilities between on-premises systems and cloud IAM platforms.

3. Third-party Risk Matches Compliance as a Top IAM Driver

Forrester revealed a pivotal shift: managing third-party identities (32%) is now equally critical as regulatory compliance (32%) in driving IAM investments. High-profile breaches at Okta and CyberArk underscore vulnerabilities introduced by third-party identities, necessitating robust governance models that go beyond basic compliance checklists.

4. Static Entitlements Are Obsolete; Zero Standing Privilege Is Now Mandatory

The static entitlement model—assigning privileges during onboarding—is officially outdated. Forrester highlighted Zero Standing Privilege (ZSP) architectures as the definitive new standard, utilizing the Continuous Access Evaluation Protocol (CAEP) to dynamically assign permissions at runtime. This strategy mitigates rampant privilege sprawl, dramatically reducing attack surfaces.

5. Identity Management Converges Across Security, Marketing, and CX

Enterprises are rapidly integrating fragmented identity management systems across marketing, customer experience (CX), fraud prevention, and security. Maxim emphasized that businesses consolidating these functions significantly improve detection speed, minimize breaches, and enhance end-user experience. Leveraging customer preference and security data together is becoming a strategic advantage.

6. Vendor Consolidation Radically Reshapes IAM Markets

IAM vendor consolidation accelerated significantly, highlighted by major moves such as Palo Alto Networks acquiring CyberArk, Ping Identity merging with ForgeRock, and CrowdStrike purchasing Adaptive Shield. Enterprises increasingly demand integrated identity platforms combining PAM, IGA, and Identity Threat Detection & Response (ITDR), driving these high-profile acquisitions.

7. Generative AI Exacerbates Identity Threats but Offers Transformational Defenses

Generative AI escalates identity threats dramatically through enhanced phishing and sophisticated deepfake impersonations. Conversely, GenAI’s defensive capabilities are equally transformative, enabling automated identity threat detection, rapid response, and real-time entitlement adjustments. Maxim described these dual dynamics as essential to future IAM strategies.

8. Machine Identities Are a Critical Emerging Attack Vector

The explosive growth in non-human identities (IoT, APIs, AI agents) vastly expands attack surfaces. Enterprises urgently need automated platforms from vendors like CyberArk, Venafi, and HashiCorp to manage this surge. Forrester highlighted machine identities as a rapidly intensifying risk requiring immediate attention and robust governance.

9. Phishing-Resistant MFA Is Dangerously Under-Deployed

Alarmingly, only 21% of companies deploy phishing-resistant MFA after breaches, despite the increasing sophistication of MFA-bypass attacks. Forrester insists enterprises must urgently adopt solutions like FIDO2 and WebAuthn. Maxim warned that neglecting these standards leaves companies dangerously exposed to credential-based compromises.

10. Context-Aware IAM Becomes a Real-time Security Necessity

Static IAM fails against machine-speed threats. Context-aware IAM, powered by dynamic authorization, continuously assesses real-time user behavior, device posture, and threat intel. Forrester identifies this adaptive approach as critical, turning identity from a passive gatekeeper to a proactive defender, which is essential for stopping attacks before damage occurs

Bottom Line: Adaptive identity security defines enterprise survival

Identity security has become synonymous with enterprise survival. Merritt Maxim’s compelling insights from Forrester’s 2025 Security & Risk Summit underscore a new identity imperative: convergence, consolidation, and context must drive strategic identity transformations. Following Forrester’s lead, enterprises must prioritize investment in dynamic Zero Standing Privilege architectures, integrated identity platforms, generative AI-enabled threat response, robust machine identity management, and phishing-resistant MFA immediately. The future of enterprise resilience hinges directly on evolving identity security today.

Nov 3

Top 10 insights from Forrester’s 2026 Cybersecurity Budget Report

“With volatility now the norm, security and risk leaders need practical guidance on managing existing spending and new budgetary necessities,” states Forrester’s 2026 Budget Planning Guide.

The research firm’s planning guide for next year provides security leaders with new insights into how their clients are allocating budgets, which gives a helpful overview of the next 12 months of cybersecurity spending.

Implicit in the guide is the need for new technologies that enable organizations to be more adaptive to threats and take action on them before they become breaches. There’s also a strong focus on getting a head start on new technologies, anticipating the severity of threats new developments in AI, generative AI (genAI), deepfakes, and all other forms of weaponized technologies can pose to an organization.

Software is a solid 40% of cybersecurity spending, exceeding hardware at 15.8%, outsourcing at 15% and surpassing personnel costs at 29% by 11 percentage points. Meanwhile, security leaders face escalating threats, with generative AI attacks executing in milliseconds, a stark contrast to the average Mean Time to Identify (MTTI) of 181 days, according to IBM’s latest Cost of a Data Breach Report.

A fast-changing threatscape is changing spending priorities

Three converging threats are flipping cybersecurity on its head. What once protected organizations is now working against them. Generative AI (gen AI) is enabling attackers to craft 10,000 personalized phishing emails per minute using scraped LinkedIn profiles and corporate communications. NIST’s 2030 quantum deadline threatens retroactive decryption of $425 billion in currently protected data. Deepfake fraud that surged 3,000% in 2024 now bypasses biometric authentication in 97% of attempts, forcing security leaders to reimagine defensive architectures fundamentally.

Top ten insights from Forrester’s 2026 cybersecurity budget benchmarks

1. Software now claims 40% of cybersecurity budgets, surpassing personnel spend. Forrester’s budget planning guide reports that software now accounts for approximately 40.2% of cybersecurity spending, eclipsing combined hardware and outsourcing budgets. It’s noteworthy that software spending is surpassing personnel costs by 11 percentage points.

2. Security budgets are accelerating, with 55% of global security and tech leaders forecasting significant increases next year. A robust 15% anticipate their budgets jumping more than 10%, and another 40% project hikes between 5% and 10%. Regional outlooks vary sharply: APAC is most bullish, with 22% expecting double-digit growth, compared to a cautious 9% in North America and just 12% in EMEA. However, nearly half (45%) remain reserved; 30% predict minimal budget bumps of 1%–4% or barely keeping pace with inflation, while another 10% expectSource: Forrester Budget Planning Guide 2026: Security and Risk no change, and 5% foresee cuts.

3. Cloud security, on-prem tech, and security awareness training are set to lead cybersecurity spending in 2026. Decision-makers are doubling down on cloud security, with 12% boosting budgets in this area by 10% or more, 11% doing the same for new on-premises solutions, and another 10% ramping up security awareness programs. Notably, investments in on-premises security technology appear twice among the top priorities, as 36% plan at least a 5% increase for both new deployments and upgrades to existing infrastructure. The numbers reflect an uneven global adoption of cloud strategies, driven by persistent concerns around cost, security, and data sovereignty. APAC is exceptionally bullish. 78% of companies there plan increased spending on new on-prem security, outpacing EMEA by 10% and North America by 8%.

4. Forrester recommends that security leaders broaden AI and ML security throughout the enterprise in 2026 as generative AI moves from standalone apps to essential business systems. Productivity suites, CRM platforms, and service tools now embed genAI natively, transforming workflows and widening potential attack surfaces. Enterprises urgently need comprehensive protection across AI models, data, applications, and user identities to counter risks such as model vulnerabilities, data leakage, and prompt jailbreaking. Hyperscalers like Google Cloud and Microsoft are responding quickly, while cybersecurity incumbents, notably Palo Alto Networks with its Protect AI acquisition, actively expand their footprint. Meanwhile, innovative startups, including Knostic and CalypsoAI, both featured at RSA’s Innovation Sandbox, target niche but critical genAI security gaps. Enterprises investing strategically now will securely scale genAI deployments and establish a clear competitive advantage.

5. Standalone SSE spending will sharply decline in 2026 as enterprises shift to unified SASE platforms, streamlining security operations and accelerating Zero Trust initiatives. Initially positioned to fill security gaps left by SD-WAN deployments and the surge in remote work, standalone SSE and isolated ZTNA solutions have now reached their functional limits. Leading companies increasingly adopt integrated platforms like Cato Networks’ cloud-native SASE, which consolidates SD-WAN, ZTNA, SWG, CASB, and firewall capabilities within a single, unified framework. As I’ve noted in VentureBeat, CISOs who pivot to unified SASE platforms benefit from simpler integration, superior AI-driven threat detection, and significant operational efficiencies that isolated solutions cannot deliver. Organizations proactively embracing integrated SASE from providers like Cato Networks will immediately enhance security resilience, improve operational agility, and significantly reduce vendor complexity.

6. Forrester predicts that by 2026, security leaders will seize a critical advantage by accelerating the adoption of post-quantum cryptography (PQC). With NIST’s landmark release of three core PQC standards in August 2024, organizations now have clear guidance to protect their data and applications against emerging quantum threats. Most governments align with NIST timelines, targeting legacy encryption deprecation by 2030, while Australia’s ASD urges adoption of approved PQC algorithms even sooner. Enterprises should immediately focus efforts on securing their most sensitive asymmetric cryptography, covering data at rest, data in transit, and data actively used within applications. Comprehensive cryptographic discovery and inventory tools provide the visibility required to assess readiness. Strategic partnerships with cryptoagility innovators, including Entrust, IBM, Keyfactor, Palo Alto Networks, QuSecure, SandboxAQ, and Thales, enable organizations to define a clear, secure migration path. Organizations acting decisively now will confidently navigate the quantum transition and fortify their competitive edge.

7. Machine identity management will become essential by 2026 as automated identities multiply rapidly across the IT infrastructure. Apps, AI agents, IoT devices, containers, cloud environments, and infrastructure scripts now generate identities faster than humans can manually track or manage. Enterprises urgently require solutions capable of managing these identities throughout their lifecycle, automating key rotations, and enforcing role-based access. Leading vendors, including Akeyless, BeyondTrust, CyberArk, Delinea, HashiCorp, Keyfactor, AppViewX, and emerging startups like Aembit, Astrix, Clutch, Entro, and Oasis Security, offer robust platforms to meet this challenge.

8. There will be a significant reallocation away from standalone interactive application security testing (IAST) in 2026, as operational hurdles continue to limit adoption. Originally designed to blend the runtime accuracy of dynamic application security testing (DAST) with static application security testing’s (SAST) code-level insights, standalone IAST has proven overly complex. Forrester recommends shifting budgets toward integrated IAST and DAST platforms, such as those from Invicti and HCLSoftware, that simplify deployment. Alternatively, APIs, microservices, and containers provide more transparent and consistent returns.

9. Consolidation of endpoint security and SIEM tools will accelerate in 2026. As extended detection and response (XDR) platforms gain momentum, security leaders have a clear opportunity to reduce agent sprawl, improve analyst efficiency, and lower the total cost of ownership. Vendors, including Microsoft, CrowdStrike, and Palo Alto Networks, now embed critical SIEM functions such as detection, correlation, third-party data ingestion (particularly from cloud, identity, and email), and response directly within their XDR offerings. While these integrated solutions currently don’t fully match standalone security analytics platforms, they deliver compelling advantages: simplified deployments, centralized threat context, and measurable operational savings. Organizations consolidating around unified XDR solutions today will streamline security operations and achieve faster, higher-quality threat detection.

10. By 2026, rapidly evolving generative AI will make deepfakes virtually indistinguishable from authentic media, rendering simplistic identity checks obsolete. Enterprises must proactively deploy sophisticated detection platforms using advanced ensemble modeling—spectral analysis, image artifacts, skin tone consistency, lighting anomalies, audio echo patterns, and device reputation, to ensure trusted employee verification and transaction authentication. Vendors such as GetReal Security, Sensity, and Reality Defender already offer real-time risk scoring, transparent reasoning, and integrated case management. Early adopters will safeguard identity security, sustain customer trust, and remain resilient against future deepfake threats.

Jul 7

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GenAI and IoT security are core to Forrester’s top 10 emerging technologies in 2024

Predicting that generative AI (genAI) for visual content, genAI for language, TuringBots, and IoT security will be the four technologies that deliver the most immediate ROI in two years, Forrester’s Top 10 Emerging Technologies In 2024 reflects the urgency more businesses have for making AI pay while securing their most at-risk endpoints.

Rounding out Forrester’s ten emerging technologies are AI agents, autonomous mobility, edge intelligence, quantum security, extended reality (XR), and Zero Trust Edge (ZTE).

Forrester’s stack ranking of technologies by ROI potential

Advising clients to include ten emerging technologies on their radar and roadmap, Forrester has segmented them into short-term, medium-, and long-term groups based on their potential to deliver ROI. Three of the ten emerging technologies are cybersecurity related.

Technologies predicted to deliver the most significant ROI over the next two years

GenAI for visual content and language. Given how quickly genAI’s adoption is accelerating across enterprises via a myriad of cloud-based apps and tools, especially in marketing, digital design, and communications, it’s clear why Forrester predicted that genAI for visual content, genAI for language have the potential to deliver ROI in two years. Forrester notes that “genAI for language is already delivering value in customer support and content creation but continues to advance at a blinding pace. It is accelerating many other technologies as it goes.”

TuringBots are predicted to accelerate app development. The report states that these AI-powered software robots “help developers build applications that deliver more than just code generation” thanks to advancements in genAI for language. TuringBots are defined as “AI-powered software that augments application development teams’ automation and semiautonomous capabilities to plan, analyze, design, code, test, deliver, and deploy while providing assistive intelligence on code, development processes, and applications.”

IoT Security to secure the proliferating number and variety of endpoint devices. Forrester defines IoT security technology as including components that are “familiar to endpoint management and security: asset management, identity and access management (IAM), data security management, Zero Trust networking, and attack surface risk management.” Forrester predicts that deploying IoT security solutions will deliver expected business value within a year as vendors increasingly offer capabilities as part of other cybersecurity platforms.

Source: Forrester’s Top 10 Emerging Technologies In 2024

Emerging technologies predicted to deliver ROI in two to five years

AI agents. Forrester is seeing AI agent technology stacks include advanced deep learning techniques, including generative, predictive, and reinforcement learning, that enable greater context, analysis, strategy, and planning. Forrester believes their full realization is two to five years away, predicting that “organizations with large amounts of information and sizable human workforces will likely see the biggest and most immediate benefits.”

Autonomous mobility. Manufacturing and logistics are two industries shifting workloads from initial pilots into production, according to Forrester. Both industries are facing continued labor shortages, regulatory pressures, and rising costs and see the potential to improve traffic and supply chain management results. Key benefits include greater operational efficiencies across shop floors, improved regulatory compliance, enhanced worker productivity and safety, and more accurate data to track environmental sustainability efforts.

Edge intelligence. Edge intelligence, according to Forrester, is “the ability to collect data, make assumptions based on that data, and link that data to relevant, distributed, orchestrated, and contextually driven responses in a network of application, device, and communication ecosystems.” The report further defines the tech stack for edge intelligence as including streaming analytics, edge ML, federated ML, and real-time data management on intelligent devices and edge servers.

Quantum security. Reducing the risk of “harvest now, decrypt later” quantum attacks, providing increased cryptographic agility for the future, and improving digital signatures are a few of the many benefits quantum security delivers. Asymmetric and symmetric key generation, symmetric key distribution via QKD, digital signatures and certificate management, and keeping an accurate list of cryptographic algorithms are some of the most common uses. These benefits and use cases form the basis of Forrestter’s assigning quantum security into the mid-segment of their stack ranking.

Source: Forrester’s Top 10 Emerging Technologies In 2024

Emerging technologies predicted to deliver ROI in over five years

Extended reality (XR). Forrester defines XR as “a technology that overlays computer imagery on a user’s field of vision, with augmented reality (AR), mixed reality, and virtual reality (VR) technologies that are supported by the same developer tools, sensors, cameras, and simulation engines.” Their report notes that only 8% of US online adults own a virtual-reality headset, and just 16% have used an augmented-reality device or app. While XR is advancing in training and onboarding, companies are resisting investing in tools like these until they see broad adoption.

Zero Trust Edge (ZTE). ZTE technology has the potential to protect remote workers, retail outlets, and branch offices with embedded local security. Highly distributed enterprises with little variation between sites are predicted to see the greatest benefit first.

Conclusion

Forrester sees security as core to any organization seeking to maximize the value and ROI of emerging technologies.

Three cybersecurity technologies, IoT security, quantum security, and zero trust edge (ZTE)—form the foundation of the ten emerging technologies. “The inclusion of these security technologies underscores a crucial point: the future belongs to those with the foresight and will to invest in security now. As AI capabilities expand, so do the potential vulnerabilities that malicious actors can exploit,” writes Brian Hopkins, vice president, emerging tech portfolio at Forrester.

Defending endpoints need to start with a zero-trust framework that enforces least privileged access and monitors everything happening on the network while also enabling microsegmentation to reduce the blast radius of a potential cyberattack. Relying on legacy account and identity and access management (IAM) systems that assume trust across systems and within identity management data structures is a breach waiting to happen.

Forrester’s top ten emerging technologies show a progression from already having significant use cases and adoption to newer technologies that are nascent in the market. All share a common characteristic with security, however. As technologies get more complex and remain unproven, security technologies need to step up the use of new technologies to counter threats. Quantum security and zero trust edge correspond with the direction of the ten emerging technologies. They reflect the need to keep improving security to protect the best ROI possible with new technologies on the horizon.

May 26

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The Most Innovative Companies of 2021 According to BCG

Apple, Alphabet, Amazon, Microsoft, and Tesla are considered the five most innovative companies, according to BCG’s analysis of the 50 most innovative companies of 2021.

Abbott Labs, AstraZeneca, Comcast, Mitsubishi, and Moderna join the top 50 most innovative companies for the first time this year.

The fastest movers include Toyota, who jumped from 41^st to 21^st; Salesforce, who jumped from 35^th to 22^nd; and Coca-Cola, who jumped from 48^th to 28^th.

90% of companies that outperform on innovation outcomes demonstrate clear C-suite ownership of the innovation agenda.

These and many other insights are from the Boston Consulting Group’s (BCG) 15^th annual report defining the world’s 50 most innovative companies in 2021. BCG surveyed 1,500 global innovation executives and found a 10% point increase, to 75%, in executives reporting that innovation is a top-three priority at their companies today. That’s the most significant year-over-year increase in the 15 global innovation surveys BCG has conducted since 2005. BCG’s Most Innovative Companies 2021: Overcoming the Innovation Readiness Gap is available for download free here (28 pp., PDF). This years’ report methodology focuses on identifying the factors causing a large innovation readiness gap between the world’s most innovative companies and their peers across industries. Please see page 23 of the study for the methodology.

Key insights from BCGs’ most innovative companies of 2020 include the following:

Creating a new COVID-19 vaccine in less than a year, inventing test kits in weeks to protect public health, and redefining online shopping and safe home delivery reflect the versatility of the world’s most innovative companies in 2021. Pzifer, Moderna, and Merck & Company’s innate ability to innovate gave everyone a decade of their lives back. Delivering a vaccine in a year when the initial projection was a decade reflects the innovative efficiency of these companies. 2021 is the first year Abbott Labs, who invented and scaled the production of COVID-19 test kits, is included in the 50 most innovative companies worldwide. Amazon and Walmart’s logistics and e-commerce expertise helped ensure safe online shopping and fast home delivery was available to millions of people under stay-at-home orders.

Five factors most differentiate the most and least innovative companies. The basis of BCG’s methodology to identify the 50 most innovative companies in 2021 centers on their innovation-to-impact (i2i) framework. The framework is designed to help companies measure the readiness of their innovation programs to operate at a consistently high level of efficiency and effectiveness. The BCG i2i scoring system identified five factors that most differentiate innovative company leaders and laggards. The five factors that best indicate how innovative a company has the potential to be are shown in the following graphic:

Lack of collaboration between sales, marketing & R&D is the major obstacle to innovation. 31% of all companies surveyed see poor collaboration between marketing and R&D as the most significant obstacle to improving the return on their innovation investments. According to BCG, the collaboration between marketing, sales, and R&D is the most challenging in the Pharmaceutical industry, where 42% of respondents say it’s the biggest hurdle to achieving more significant returns on innovation.

Digital transformation of the core business is now a top priority for 75% of CEOs, and 65% of firms are doubling down on their plans for transformation with renewed urgency. BCG identified six success factors that together—and only together—flip the odds of digital transformation success from 30% to 80%. Those six success factors are close integration of digital strategy with the business strategy, commitment from the CEO through middle management, a talent core of digital superstars, business-led and flexible technology and data platforms, agile governance, and effective monitoring of progress toward defined outcomes.

Conclusion

Companies that know how to collaborate quickly between customer and R&D teams have an inside edge on being innovation leaders. The world’s most innovative companies also have senior management teams committed to the long-term success of nascent, unproven programs. There’s greater tolerance for risk, more of a focus on customers first and innovating around their needs, and an intuitive sense of how to close innovation gaps that hold other companies back.

Feb 28

Securing Machine Identities Needs To Be A Top Cybersecurity Goal In 2021

Bottom Line: Bad actors quickly capitalize on the wide gaps in machine identity security, creating one of the most breachable threat surfaces today.

Why Machines Are the Most Challenging Threat Surface To Protect

Forrester’s recent webinar on the topic, How To Secure And Govern Non-Human Identities, estimates that machine identities (including bots, robots and IoT) are growing twice as fast as human identities on organizational networks. Forrester defines machine, or non-human, identities as robotic process automation (bots), robots (industrial, enterprise, medical, military) and IoT devices.

The webinar points out that one of the fastest-growing automation types is software bots, with 36% used in finance and accounting, 15% used in business line and 15% in IT. The webinar also points out that in 2019, there were 2.25 million robots in the global workforce, twice as many as in 2010 and 32% of global infrastructure decision-makers expect their firms to use robotic process automation (RPA) over the next 12 months.

According to the Forrester Consulting white paper, Securing The Enterprise With Machine Identity Protection, over 50% of organizations find it challenging to protect their machine identities today. Unprotected machine identities are making it easy for bad actors to take control of entire networks of devices. Bad actors rely on organizations’ bots to provide the cover they need to attack networks and devices, often undetected for months or years.

Forrester found that machine identities are left exposed to bad actors because organizations aren’t adopting the tools they need to create and manage a centralized Identity Access Management (IAM) strategy across all machines. This includes defining and enforcing policies, auditing each machine and endpoint and better integrating support across machines and monitoring systems.

Furthermore, by adopting a more modern Privileged Identity Management (PIM) approach, organizations could solve many of these challenges. Leading PIM solutions providers include Centrify, which has succeeded in adapting to the ephemeral nature of securing machine identities by delivering machine identity and credential authentication based on a centralized trust model.

The Forrester report’s bottom line is that machines are isolated, exposed and more vulnerable than any other endpoint on a network. The following graphic compares protection strategies and finds a majority of organizations struggling to deliver them:

Securing Machine Identities Needs To Be a Top Cybersecurity Goal In 2021

Machine Identities Are Networks’ Weakest Security Link

According to a Venafi study, machine identity attacks grew 400% between 2018 and 2019, increasing by over 700% between 2014 and 2019. Malware capable of compromising machine identities continues to gain momentum, doubling between 2018 and 2019 and growing 300% over the five years leading up to 2019. According to Kount’s 2020 Bot Landscape and Impact Report, 81% of enterprises are regularly dealing with malicious bots today and one in four say a single bot attack has cost them $500,000 or more. Furthermore, many organizations may not realize how many bots and machine identities they have – and bad actors capable of creating hundreds using automated scripting tools.

Forrester provided the following data points underscoring how vulnerable machines are to botnet and identity-based attacks today:

The 2017 Mirai botnet attack is a cautionary tale of the dangers of using default security credentials on machines and IoT devices. Using botnets to automate scans of vast blocks of IP addresses for potential telnet ports to log into, the Mirai botnets were programmed to rapidly try a series of basic usernames and passwords to gain access to IoT devices and machines. The Mirai botnets were successful, gaining control of thousands of machines and orchestrating them to deliver one of the largest DDOS attacks in history.
It’s common for enterprises to lose track of how many bots they’ve created, giving malicious actors the perfect cover to mask their movements. Instead of creating their bots, malicious actors look to disguise their movements across a network with a company’s bots. Forrester’s webinar mentioned how a large North American insurance provider deployed 400 software bots for customer-facing digital chatbots and processing claims, among other tasks.
There’s often no oversight of who has the rights to create and launch bots internally, leading to potentially thousands of bots without secured identities. One of the most troubling findings presented during the webinar is how loose the process is to create a bot – with no checks and balances in place or means of achieving consistent identity management.

How To Strengthen Machine Security

The more challenging any machine threat surface is to protect, the more opportunity it provides bad actors to breach them. A good place to start is by clarifying who owns keeping Transport Layer Security (TLS) and previous-generation Secured-Sockets Layer (SSL) client and server certificates, code signing certificates, Secure Shell (SSH) host and cryptographic keys so they are kept up to date. Letting those fall through the cracks will leave thousands of machines exposed and exploitable on networks.

Prioritizing machine identities and securing machine credentials is a must-have in 2021, as botnet attacks are quickly increasing due to bad actors’ being able to spin up thousands of them in days. The following are key steps to get started:

Taking a Zero Trust approach to managing every machine identity authentication on a network now could save thousands of hours and dollars in the future. Taking a least privilege access approach to managing machines now will pay off in the future, as the workloads of machines and non-human entities continue to grow more complex. The Forrester webinar expands on this point by explaining how new, more complex inter-machine relationships are evolving quicker than legacy approaches to endpoint governance and security can keep up.
Privileged access controls need to be more adaptive, secure and scalable than many organizations’ static-based approaches to securing machines are today. Forrester recommends replacing long-standing hardcoded credentials with session-based ones assigned via API calls from a vault. Machines are being used 24/7 and have access patterns completely different from humans using the network, making dynamically-assigned, ephemeral credentials even more important to protect a network. Privileged Identity Management (PIM) proves effective at providing privileged access controls for machine identities, with Forrester mentioning Centrify, HashiCorp and others as leaders in this area. Centrify’s approach is noteworthy in enrolling machines with its platform via a client to establish a trust relationship, so applications running on that machine can also be authenticated using a short-lived, scoped token.
Monitoring more machines on a network often leads to a transition from legacy to integrated log monitoring systems that can capture, analyze and report anomalous activity across a network. Log Monitoring systems are proving invaluable in identifying machine endpoint configuration and performance anomalies in real-time. AIOps is proving effective in identifying anomalies and performance event correlations in real-time, contributing to greater business continuity. One of the leaders in this area is LogicMonitor, whose AIOps-enabled infrastructure monitoring and observability platform have proven successful in troubleshooting infrastructure problems and ensuring business continuity.
Perform periodic audits to track all bots and machines in use across an organization, using Microsoft Active Directory to inventory and manage all of them. One of the most valuable take-aways from the Forrester webinar is the need to manage machine identities and their credentials centrally. Forrester mentions Microsoft Active Directory as one option. The companies providing services in this area include Centrify, which pioneered Active Directory bridging to authenticate human and machine identities based on a centralized model from a single identity repository.

Conclusion

Machines, or as Forrester calls them in their webinar, non-human identities require more precise, adaptive and ephemeral identity structures and access controls. CISOs and CIOs need to take greater ownership of machine identity authentication and provide Identity Access Management (IAM) and Privileged Access Management (PAM) down to the bot and non-human identity level. With the exponential growth of malicious bots tracking machine identities, now is the time to place machine identities among the highest priority of any cybersecurity strategy in 2021.

Mar 8

What You Need To Know About Location Intelligence In 2020

53% of enterprises say that Location Intelligence is either critically important or very important to achieving their goals for 2020.
Leading analytics and platform vendors who offer Location Intelligence include Alteryx, Microsoft, Qlik, SAS, Tableau and TIBCO Software.
Location Intelligence vendors providing specialized apps and platforms include CARTO, ESRI, Galigeo, MapLarge, and Pitney Bowes.
Product Managers need to consider how adding Location Intelligence can improve the contextual accuracy of marketing, sales, and customer service apps and platforms.
Marketers need to look at how they can capitalize on smartphones’ prolific amounts of location data for improving advertising, buying, and service experiences for customers.
R&D, Operations, and Executive Management lead all other departments in their adoption and use of Location Intelligence this year.
Enterprises favor cloud-based Location Intelligence deployments in 2020, with on-premise deployments also seeing new sales this year.

These and many other fascinating insights are from Dresner Advisory Services’ 2020 Location Intelligence Market Study, their 7^th annual report that examines enterprise end-users’ requirements and features including geocoding support, location intelligence visualization, analytics capabilities, and third-party GIS integration. The study is noteworthy for its depth of insights into industry adoption of Location Intelligence and how user requirements drive industry capabilities. Dresner Advisory Services defines location intelligence as a form of Business Intelligence (BI), where the dominant dimension used for analysis is location or geography. Most typically, though not exclusively, analyses are conducted by viewing data points overlaid onto an interactive map interface.

“When we began covering Location Intelligence in 2014, we saw the potential for the topic to gain mainstream interest,” said Howard Dresner, founder, and chief research officer at Dresner Advisory Services. “With the growth in visualization and the emergence of the Internet of Things (IoT), incorporating maps and location into business analyses have become increasingly important to many organizations.” Please see page 11 for a description of the methodology and page 13 for an overview of study demographics. Wisdom of Crowds® research is based on data collected on usage and deployment trends, products, and vendors.

Key insights from the study that provides an excellent background on the current state of location intelligence in 2020 include the following:

R&D, Operations, and Executive Management lead all enterprise areas in adoption with Location Intelligence being considered critical to their ongoing operations. The majority of Marketing & Sales leaders see Location Intelligence as very important to their ongoing operations. The following graphic compares how important Location Intelligence is to each of the seven departments included in the survey:

What You Need To Know About Location Intelligence In 2020

90% of Government organizations consider Location Intelligence to be critical or very important to their ongoing operations. Healthcare providers have the second-highest number of organizations who rate Location Intelligence as critical. The study found that mean importance levels are similar across Business Services, Financial Services, Manufacturing, and Consumer Services organizations and decline further among Technology, Retail/Wholesale, and Higher Education segments.

Data visualization/mapping dominates all other Location Intelligence use cases in 2020, with over 70% of organizations considering it critical or very important to accomplishing their goals. The study found that the majority of other use cases haven’t achieved the broad adoption data visualization & mapping has. Despite the lower levels of criticality assigned to the nine other use cases, they each show the potential to streamline essential marketing, sales, and operational areas of an enterprise. Site planning/site selection, geomarketing, territory management/optimization, and logistics optimization make up a tier of secondary interest that taken together streamlines supply chains while making an organization easier to buy from. The Dresner research team also defines the third tier of use cases led by fleet routing and citizen services, followed by IoT & smart cities, indoor mapping, and real estate investment/pricing analysis. Despite IoT being over-promoted by vendors, just over 50% of enterprises say the technology is not important to them at this time. The following graphic compares Location Intelligence use cases by the level of criticality as defined by responding organizations:

R&D leads all departments in data visualization/mapping adoption, reflecting the high level of importance this use case has across entire enterprises as well. Additional departments and functional areas relying on data visualization/mapping include Operations, Business Intelligence Competency Center (BICC), and Executive Management. Geomarketing is seeing the most significant adoption in Marketing & Sales. Operations lead all other functional areas in the adoption of logistics optimization and fleet routing use cases. Dresner’s research team found that R&D’s interest in Location Intelligence, which varies across use cases, may reflect the use of packaged applications as well as select custom development.

Map-based visualization, dashboard inclusion of maps, and drill-down navigation through map interfaces are the three highest priority features enterprises look for today. These three features are considered very important to between 64% to 67% of leaders interviewed. Layered visualizations, multi-layer support, and custom region definition are the next most important features. The following graphic provides an overview of prioritized Location intelligence visualization features.

Executive Management, BICC, and Operations have the highest level of interest in map-based visualizations that further accelerate the adoption of Location Intelligence across enterprises. Executive Management also leads all others in their interest in dashboard inclusion of maps and custom map support. Executive Management’s increasing adoption of multiple Location intelligence use cases is a catalyst driving greater enterprise-wide adoption. R&D’s prioritizing the layering of visualizations on top of maps, offline mapping and animation of data on maps are leading indicators of these use cases attaining greater enterprise adoption in future years.

Four of the top ten Location Intelligence features are considered very important/critical to enterprises, reflecting a maturing market. The most popular (counting, quantifying, or grouping) is critical or very important to 46% of organizations and at least important to nearly 70%. Another indicator of how quickly Location Intelligence is maturing in enterprises is the advanced nature of analytics features being relied on today. Predicting trends and volatility, detecting clusters and outliers, and measuring distances reflect how multiple departments in enterprises are collaborating using Location Intelligence to achieve their shared goals.

Government dominates the use of data visualization/mapping with a strong interest in site planning/site selection, citizen services, fleet routing, and territory management. Business Services are most interested in using Location Intelligence for Indoor Mapping and IoT & Smart Cities. Geomarketing is the most adopted feature in Higher Education, Financial Services, Healthcare, and Retail/Wholesale. Manufacturing and Retail/Wholesale lead all other industries in their adoption of Logistics Optimization. The following graphic provides insights into Location Intelligence use case by industry:

Executive Management and Business Intelligence Competency Centers (BICC) most prioritize Location Intelligence applications that have built-in or native geocoding. Enterprises are looking at how built-in or native geocoding can scale across their Location Intelligence use cases and broader BI strategy with Executive Management taking the lead on achieving this goal. Automated geocoding support and street-level geocoding support are also a high priority to Executive Management. Marketing/Sales lead all other departments in their interest in geofencing/reverse geofencing, indicating enterprises are beginning to use these geocoding features to achieve greater accuracy in their marketing and selling strategies. It’s interesting to note that geofencing/reverse geofencing has progressed from R&D in previous studies to Marketing/Sales putting the highest priority on it today. Dresner’s research team interprets the shift to customer-facing strategies being an indicator of broader enterprise adoption for geofencing/reverse geofencing.

61% of organizations say Google integration is essential to their Location Intelligence strategies. Google continues to dominate organizations’ roadmaps as the integration of choice for adding more GIS data to Location Intelligence strategies. ESRI is the second choice with 45% of organizations naming it as an integration requirement. Database extensions (30%) are the next most cited, followed by OpenStreetMap (20%). All other choices are requirements at less than 20% of organizations.

Nov 27

Predicting The Future Of Digital Marketplaces

The U.S. B2B eCommerce market is predicted to be worth $1.2T by 2022 according to Forrester.
75% of marketing executives say that reaching customers where they prefer to buy is the leading benefit a company gains from selling through an e-commerce marketplace according to Statista.
67% strongly agree to the importance of B2B e-commerce being critical to their business’s advantages and results in their industry.

Digital Marketplaces are flourishing today thanks to the advances made in Artificial Intelligence (AI), machine learning, real-time personalization and the scale and speed of the latest generation of cloud platforms including the Google Cloud Platform. Today’s digital marketplaces are capitalizing on these technologies to create trusted, virtual trading platforms and environments buyers and sellers rely on for a wide variety of tasks every day.

Differentiated from B2B exchanges and communities from the 90s that often had high transaction costs, proprietary messaging protocols, and limited functionality, today’s marketplaces are proving that secure, trusted scalability is achievable on standard cloud platforms. Kahuna recently partnered with Brian Solis of The Altimeter Group to produce a fascinating research study, The State (and Future) of Digital Marketplaces. The report is downloadable here (PDF, 14 pp., opt-in). A summary of the results is presented below.

Kahuna Digitally Transforms Marketplaces With Personalization

The essence of any successful digital transformation strategy is personalization, and to the extent, any organization can redefine every system, process, and product to that goal is the extent to which they’ll grow. Digital marketplaces are giving long-established business and startups a platform to accelerate their digital transformation efforts by delivering personalization at scale.

Kahuna’s approach to solving personalization at scale across buyers and sellers while creating trust in every transaction reflects the future of digital marketplaces. They’ve been able to successfully integrate AI, machine learning, advanced query techniques and a cloud platform that scales dynamically to handle unplanned 5x global traffic spikes. Kahuna built its marketplace platform on Google App Engine, Google BigQuery, and other Google Cloud Platform (GCP).

Kahuna’s architecture on GCP has been able to scale and onboard 80+ million users a day without any DevOps support, a feat not possible with the exchange and community platforms of the 90s. By integrating their machine learning algorithms designed to enhance their customers’ ability to personalize marketing messages with Google machine learning APIs to drive TensorFlow, Kahuna has been able to deliver fast response times to customers’ inquiries. Their latest product, Kahuna Subject Line Optimization, analyzes the billions of emails their customers use to communicate with customers to see what has and hasn’t worked in the past. Marketplace customers will receive real-time recommendations as they are in the email editor composing an email subject line. Kahuna scores the likely success of the subject lines in appealing to target audiences so that marketers can make adjustments on the fly.

The State (And Future) Of Digital Marketplaces

Digital marketplaces are rapidly transforming from transaction engines to platforms that deliver unique, memorable and trusted personal experiences.
Anyone who has ever used OpenTable to get a last-minute reservation with friends at popular, crowded restaurant has seen the power of digitally enabled marketplace experiences in action. Brian Solis noted futurist, author, and analyst with The Altimeter Group recent report, The State (and Future) of Digital Marketplaces is based on 100 interviews with North American marketing executives across eight market segments.
Key insights and lessons learned from the study include the following:

Altimeter found that 67% of marketplaces are generating more than $50M annually and 32% are generating more than $100M annually with the majority of marketplaces reporting a Gross Merchandise Volume (GMV) of between $500M to $999M. When the size of participating companies is taken into account, it’s clear digital marketplaces are one form of new digital business models larger organizations are adopting, piloting and beginning to standardize on. It can be inferred from the data that fast-growing, forward-thinking smaller organizations are looking to digital marketplaces to help augment their business models. Gross merchandise volume (GMV) is the total value of merchandise sold to customers through a marketplace.
59% of marketing executives say new product/service launches are their most important marketplace objective for 2019. As marketplaces provide an opportunity to create an entirely new business model, marketing executives are focused on how to get first product launches delivering revenue fast. Revenue growth (55%), customer acquisition (54%) and margin improvement (46%) follow in priority, all consistent with an organizations’ strategy of relying on digital marketplaces as new business models.

Competitive differentiation, buyer retention, buyer acquisition, and social media engagement and the four most common customer-facing challenges marketplaces face today. 39% of marketing execs say that differentiating from competitors is the greatest challenge, followed by buyer retention (32%), buyer acquisition (29%) and effective social media campaigns (29%) Further validation that today’s digital marketplaces are enabling greater digital transformation through personalization is found in just 22% of respondents said customer experience is a challenge.
Marketplaces need to scale and provide a broader base of services that enable “growth as a ” to keep sellers engaged. Marketplaces need to continually be providing new services and adding value to buyers and sellers, fueling growth-as-a-service. The three main reasons sellers leave a marketplace are insufficient competitive differentiation (46%), insufficient sales (33%) and marketplace service fees (31%). Additionally, sellers claim that marketing costs (28%) and the lack of buyers (26%) are critical business issues.
Lack of sellers who meet their needs (53%) is the single biggest reason buyers leave marketplaces. Buyers also abandon marketplaces due to logistical challenges including shipping costs and fees added by sellers (49%) and large geographic distances between buyers and sellers (39%). These findings underscore why marketplaces need to be very adept at creating and launching new value-added services and experiences that keep buyers active and loyal. Equally important is a robust roadmap of seller services that continually enables greater sales effectiveness and revenue potential.

Nov 17

The State Of IoT Intelligence, 2018

Sales, Marketing and Operations are most active early adopters of IoT today.
Early adopters most often initiate pilots to drive revenue and gain operational efficiencies faster than anticipated.
32% of enterprises are investing in IoT, and 48% are planning to in 2019.
IoT early adopters lead their industries in advanced and predictive analytics adoption.

These and many other fascinating insights are from Dresner Advisory Services’ latest report, 2018 IoT Intelligence^®Market Study, in its 4^th year of publication. The study concentrates on end-user interest in and demand for business intelligence in IoT. The study also examines key related technologies such as location intelligence, end-user data preparation, cloud computing, advanced and predictive analytics, and big data analytics. “While the market is still in an early stage, we believe that IoT Intelligence, the means to understand and leverage IoT data, will continue to expand as organizations mature in their collection and leverage of sensor level data,” said Howard Dresner, founder, and chief research officer at Dresner Advisory Services. 70% of respondents work at North American organizations (including the United States, Canada, and Puerto Rico). EMEA accounts for about 20%, and the remainder is distributed across Asia-Pacific and Latin America. Please see pages 11, 15 through 18 of the study for specifics regarding the methodology and respondent demographics.

Key insights gained from the study include the following:

Sales, Marketing and Operations are most active early adopters of IoT today. Looking to capitalize on IoT’s potential to gain real-time customer feedback on products’ and services’ performance, Sales and Marketing lead all departments in their prioritizing IoT’s value in the enterprises. 12% of Operations leaders say that IoT is critical to attaining their goals. Executive Management and Finance have yet to see the value that Sales, Marketing and Operations do.

Manufacturers see IoT as the most critical to achieving their product quality, production scheduling and supply chain orchestration goals. Insurance industry leaders also view IoT as critical to operations as their business models are now concentrating on automating inventory and safety management. Insurance firms also track vehicles in shipping and logistics fleets to gain greater visibility into how route operations can be optimized at the lowest possible risk of accidents. Financial Services and Healthcare are the next most interested in IoT with Higher Education and Business Services assign the lowest levels of importance by industry.

Investment in IoT analytics, application development and defining accurate, reliable metrics to guide development is the most critical aspect of IoT adoption today. Investments in the data supply chain including data capture, movement, data prep, and management is the second-most critical area followed by investments in IoT infrastructure. Analytics, application development, and accurate, reliable metrics guiding DevOps are consistent with the study’s finding that early adopters have an excellent track record adopting and applying advanced and predictive analytics to challenging logistical, operations, sales, and marketing problems.

IoT early adopters or advocates prioritize dashboards, reporting, IoT use cases that provide data streams integral to analytics, advanced visualization, and data mining. IoT early adopters and the broader respondent base differ most in the prioritization of IT analytics, location intelligence, integration with operational processes, in-memory analysis, open source software, and edge computing. The data reflects how IoT early adopters quickly become more conversant in emerging technologies with the goal of achieving exponential scale across analytics and IoT platforms.

The criticality of advanced and predictive analytics to all leaders surveyed is at an all-time high. Attaining a (weighted-mean) importance score of 3.6 on a 5.0 scale, advanced and predictive analytics is today considered “critical” or “very important” to a majority of respondents. Despite a mild decline in 2017, importance sentiment (the perceived criticality of advanced and predictive analytics) is on an uptrend across the five years of our study. Mastery of advanced and predictive analytics is a leading indicator of IoT adoption, indicating the potential for more analytics pilots and in-production IoT projects next year.

The most valuable features for advanced and predictive analytics apps include support for a range of regression models, hierarchical clustering, descriptive statistics, and recommendation engine support. Model management is important to more than 90% of respondents, further indicating IoT analytics scale is a goal many are pursuing. Geospatial analysis (highly associated with mapping, populations, demographics, and other web-generated data), Bayesian methods, and automatic feature selection is the next most required series of features.

Access to advanced analytics for predictive and temporal analysis is the most important usability benefit to IoT adopters today. Second is support for easy iteration, and third is a simple process for continuous modification of models. The study evaluated a detailed set of nine usability benefits that support advanced and predictive activities and processes. All nine benefits are important to respondents, with the last one of a specialist not being required important to a majority of them at 70%.

Jul 4

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Where Business Intelligence Is Delivering Value In 2018

Executive Management, Operations, and Sales are the three primary roles driving Business Intelligence (BI) adoption in 2018.
Dashboards, reporting, end-user self-service, advanced visualization, and data warehousing are the top five most important technologies and initiatives strategic to BI in 2018.
Small organizations with up to 100 employees have the highest rate of BI penetration or adoption in 2018.
Organizations successful with analytics and BI apps define success in business results, while unsuccessful organizations concentrate on adoption rate first.
50% of vendors offer perpetual on-premises licensing in 2018, a notable decline over 2017. The number of vendors offering subscription licensing continues to grow for both on-premises and public cloud models.
Fewer than 15% of respondent organizations have a Chief Data Officer, and only about 10% have a Chief Analytics Officer today.

These and many other fascinating insights are from Dresner Advisory Service’s 2018 Wisdom of Crowds® Business Intelligence Market Study. In its ninth annual edition, the study provides a broad assessment of the business intelligence (BI) market and a comprehensive look at key user trends, attitudes, and intentions. The latest edition of the study adds Information Technology (IT) analytics, sales planning, and GDPR, bringing the total to 36 topics under study.

“The Wisdom of Crowds BI Market Study is the cornerstone of our annual research agenda, providing the most in-depth and data-rich portrait of the state of the BI market,” said Howard Dresner, founder and chief research officer at Dresner Advisory Services. “Drawn from the first-person perspective of users throughout all industries, geographies, and organization sizes, who are involved in varying aspects of BI projects, our report provides a unique look at the drivers of and success with BI.” Survey respondents include IT (28%), followed by Executive Management (22%), and Finance (19%). Sales/Marketing (8%) and the Business Intelligence Competency Center (BICC) (7%). Please see page 15 of the study for specifics on the methodology.

Key takeaways from the study include the following:

Executive Management, Operations, and Sales are the three primary roles driving Business Intelligence (BI) adoption in 2018. Executive management teams are taking more of an active ownership role in BI initiatives in 2018, as this group replaced Operations as the leading department driving BI adoption this year. The study found that the greatest percentage change in functional areas driving BI adoption includes Human Resources (7.3%), Marketing (5.9%), BICC (5.1%) and Sales (5%).

Making better decisions, improving operational efficiencies, growing revenues and increased competitive advantage are the top four BI objectives organizations have today. Additional goals include enhancing customer service and attaining greater degrees of compliance and risk management. The graph below rank orders the importance of BI objectives in 2018 compared to the percent change in BI objectives between 2017 and 2018. Enhanced customer service is the fastest growing objective enterprises adopt BI to accomplish, followed by growth in revenue (5.4%).

Dashboards, reporting, end-user self-service, advanced visualization, and data warehousing are the top five most important technologies and initiatives strategic to BI in 2018. The study found that second-tier initiatives including data discovery, data mining/advanced algorithms, data storytelling, integration with operational processes, and enterprise and sales planning are also critical or very important to enterprises participating in the survey. Technology areas being hyped heavily today including the Internet of Things, cognitive BI, and in-memory analysis are relatively low in the rankings as of today, yet are growing. Edge computing increased 32% as a priority between 2017 and 2018 for example. The results indicate the core aspect of excelling at using BI to drive better business decisions and more revenue still dominate the priorities of most businesses today.
Sales & Marketing, Business Intelligence Competency Center (BICC) and Executive Management have the highest level of interest in dashboards and advanced visualization. Finance has the greatest interest in enterprise planning and budgeting. Operations including manufacturing, supply chain management, and services) leads interest in data mining, data storytelling, integration with operational processes, mobile device support, data catalog and several other technologies and initiatives. It’s understandable that BICC leaders most advocate end-user self-service and attach high importance to many other categories as they are internal service bureaus to all departments in an enterprise. It’s been my experience that BICCs are always looking for ways to scale BI adoption and enable every department to gain greater value from analytics and BI apps. BICCs in the best run companies are knowledge hubs that encourage and educate all departments on how to excel with analytics and BI.

Insurance companies most prioritize dashboards, reporting, end-user self-service, data warehousing, data discovery and data mining. Business Services lead the adoption of advanced visualization, data storytelling, and embedded BI. Manufacturing most prioritizes sales planning and enterprise planning but trails in other high-ranking priorities. Technology prioritizes Software-as-a-Service (SaaS) given its scale and speed advantages. The retail & wholesale industry is going through an analytics and customer experience revolution today. Retailers and wholesalers lead all others in data catalog adoption and mobile device support.

Insurance, Technology and Business Services vertical industries have the highest rate of BI adoption today. The Insurance industry leads all others in BI adoption, followed by the Technology industry with 40% of organizations having 41% or greater adoption or penetration. Industries whose BI adoption is above average include Business Services and Retail & Wholesale. The following graphic illustrates penetration or adoption of Business Intelligence solutions today by industry.

Dashboards, reporting, advanced visualization, and data warehousing are the highest priority investment areas for companies whose budgets increased from 2017 to 2018. Additional high priority areas of investment include advanced visualization and data warehousing. The study found that less well-funded organizations are most likely to lead all others by investing in open source software to reduce costs.

Small organizations with up to 100 employees have the highest rate of BI penetration or adoption in 2018. Factors contributing to the high adoption rate for BI in small businesses include business models that need advanced analytics to function and scale, employees with the latest analytics and BI skills being hired to also scale high growth businesses and fewer barriers to adoption compared to larger enterprises. BI adoption tends to be more pervasive in small businesses as a greater percentage of employees are using analytics and BI apps daily.

Executive Management is most familiar with the type and number of BI tools in use across the organization. The majority of executive management respondents say their teams are using between one or two BI tools today. Business Intelligence Competency Centers (BICC) consistently report a higher number of BI tools in use than other functional areas given their heavy involvement in all phases of analytics and BI project execution. IT, Sales & Marketing and Finance are likely to have more BI tools in use than Operations.

Enterprises rate BI application usability and product quality & reliability at an all-time high in 2018. Other areas of major improvements on the part of vendors include improving ease of implementation, online training, forums and documentation, and completeness of functionality. Dresner’s research team found between 2017 and 2018 integration of components within product dropped, in addition to scalability. The study concludes the drop in integration expertise is due to an increasing number of software company acquisitions aggregating dissimilar products together from different platforms.

Jun 30

Artificial Intelligence Will Enable 38% Profit Gains By 2035

By 2035 AI technologies have the potential to increase productivity 40% or more.
AI will increase economic growth an average of 1.7% across 16 industries by 2035.
Information and Communication, Manufacturing and Financial Services will be the top three industries that gain economic growth in 2035 from AI’s benefits.
AI will have the most positive effect on Education, Accommodation and Food Services and Construction industry profitability in 2035.

Today Accenture Research and Frontier Economics published How AI Boosts Industry Profits and Innovation. The report is downloadable here (28 pp., PDF, no opt-in).The research compares the economic growth rates of 16 industries, projecting the impact of Artifical Intelligence (AI) on global economic growth through 2035. Using Gross Value Added (GVA) as a close approximation of Gross Domestic Product (GDP), the study found that the more integrated AI is into economic processes, the greater potential for economic growth. One of the reports’ noteworthy findings is that AI has the potential to increase economic growth rates by a weighted average of 1.7% across all industries through 2035. Information and Communication (4.8%), Manufacturing (4.4%) and Financial Services (4.3%) are the three sectors that will see the highest annual GVA growth rates driven by AI in 2035. The bottom line is that AI has the potential to boost profitability an average of 38% by 2035 and lead to an economic boost of $14T across 16 industries in 12 economies by 2035.

Key takeaways from the study include the following:

AI will increase economic growth by an average of 1.7% across 16 industries by 2035 with Information and Communication, manufacturing and financial services leading all industries. Accenture Research found that the Information and Communication industry has the greatest potential for economic growth from AI. Integrating AI into legacy information and communications systems will deliver significant cost, time and process-related savings quickly. Accenture predicts the time, cost and labor savings will generate up to $4.7T in GVA value in 2035. High growth areas within this industry are cloud, network, and systems security including defining enterprise-wide cloud security strategies.

AI will most increase profitability in Education, Accommodation and Food Services and Construction industries in 2035. Personalized learning programs and automating mundane, routine tasks to free up colleges, universities, and trade school instructors to teach new learning frameworks will accelerate profitability in the education through 2035. Accommodation & Food Services and Construction are industries with manually-intensive, often isolated processes that will benefit from the increased insights and contextual intelligence from AI throughout the forecast period.

Manufacturing’s adoption of Industrial Internet of Things (IIoT), smart factories and comparable initiatives are powerful catalysts driving AI adoption. Based on the proliferation of Industrial Internet of Things (IIoT) devices and the networks and terabytes of data they generate, Accenture predicts AI will contribute an additional $3.76T GVA to manufacturing by 2035. Supply chain management, forecasting, inventory optimization and production scheduling are all areas AI can make immediate contributions to this industry’s profits and long-term economic

Financial Services’ greatest gains from AI will come automating and reducing the errors in mundane, manually-intensive tasks including credit scoring and first-level customer inquiries. Accenture forecasts financial services will benefit $1.2T in additional GVA in 2035 from AI. Follow-on areas of automation in Financial Services include automating market research queries through intelligent bots, and scoring and reviewing mortgages.

By 2035 AI technologies could increase labor productivity 40% or more, doubling economic growth in 12 developed nations. Accenture finds that AI’s immediate impact on profitability is improving individual efficiency and productivity. The economies of the U.S. and Finland are projected to see the greatest economic gains from AI through 2035, with each attaining 2% higher GVA growth.The following graphic compares the 12 nations included in the first phase of the research.

Sources:

Accenture Report: Artificial Intelligence Has Potential to Increase Corporate Profitability in 16 Industries by an Average of 38 Percent by 2035

Accenture: How AI Boosts Industry Profits And Innovation

Researching the intersection of AI, machine learning and cybersecurity in the enterprise

Posts from the ‘Analyst Research: Forrester & IDC’ Category

1. Identity Security Budgets Accelerate Toward $27.5B by 2029

2. Hybrid IAM Still Dominates—77% Keep On-Premise Components

3. Third-party Risk Matches Compliance as a Top IAM Driver

4. Static Entitlements Are Obsolete; Zero Standing Privilege Is Now Mandatory

5. Identity Management Converges Across Security, Marketing, and CX

6. Vendor Consolidation Radically Reshapes IAM Markets

7. Generative AI Exacerbates Identity Threats but Offers Transformational Defenses

8. Machine Identities Are a Critical Emerging Attack Vector

9. Phishing-Resistant MFA Is Dangerously Under-Deployed

10. Context-Aware IAM Becomes a Real-time Security Necessity

Bottom Line: Adaptive identity security defines enterprise survival

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A fast-changing threatscape is changing spending priorities

Top ten insights from Forrester’s 2026 cybersecurity budget benchmarks

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Forrester’s stack ranking of technologies by ROI potential

Technologies predicted to deliver the most significant ROI over the next two years

Emerging technologies predicted to deliver ROI in two to five years

Emerging technologies predicted to deliver ROI in over five years

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