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Posts from the ‘gen AI’ Category

Oct 19

Gartner’s 13 ways GenAI is improving B2B Sales is the roadmap every business needs

Gartner's 13 ways GenAI is improving B2B Sales is the roadmap every business needs

Generative AI (GenAI) ‘s potential for streamlining the most time-consuming processes in B2B sales is just getting started. As businesses increasingly rely on AI to enhance efficiency, automate routine tasks, and personalize customer engagement, GenAI is set to become a critical differentiator in the race for B2B sales and market leadership.

  • B2B sales organizations using GenAI-embedded sales technologies will reduce the time they spend prospecting and preparing for customer meetings by over 50% within two years.
  • Conversational interfaces based on GenAI will gain momentum and further revolutionize B2B selling. In 2028, they will be the driving force behind up to 60% of B2B sales interactions, up from less than 5% in 2023.
  • Centralized GenAI operations teams are also on the way, championed by Chief Revenue Officers (CROs). These teams will focus on integrating AI-driven strategies into sales and revenue operations. 35% of CROs will have GenAI operations teams online and incorporated into their companies’ strategic planning process by 2025.

The goal: find the most likely wins for GenAI in B2B Sales

Gartner’s recent report, 13 Generative AI Use Cases for B2B Sales, provides an analysis of where GenAI is helping improve B2B sales now and in the future.

“Generative artificial intelligence (GenAI) is reshaping the sales technology landscape, offering innovative solutions in areas such as prospecting, sales analytics, forecasting, and sales enablement. Tools infused with GenAI capabilities are embedded in use cases across the sales function, supporting key priorities such as revenue growth, GTM, cost optimization, and risk mitigation,” write the authors of Gartner’s study.

In defining and ranking the most valuable use cases of GenAI in B2B sales, Gartner examined where the technology is being most effectively applied to improve sales operations, increase seller productivity, and fuel future transformation.

The following multidimensional grid defines the use cases by value and feasibility.

Source: Generative AI Use Cases for B2B Sales, Gartner, Inc.

Gartner evaluated each use case for GenAI in B2B sales by scoring them on two key factors: business value and feasibility. The figure below shows the breakout of value and feasibility factors Gartner has used as a framework to rank the 13 use cases: “While we’ve defined the dimensions of value and feasibility according to our research criteria, companies are encouraged to customize these parameters to align with their own business needs,” the report states.

Source: Gartner, Inc. (2024) Generative AI Use Cases for B2B Sales

Mapping GenAI Use Cases Across Business Functions

Gartner also provides a GenAI use-case pipeline as part of their analysis to graphically explain how the 13 AI-driven strategies or use cases are distributed across business functions, including marketing, sales, and customer success.

The goal is to help organizations identify and take action on the use cases that will deliver the most significant potential impact. Gartner advises that use cases that span multiple stages of the pipeline typically deliver greater overall business value, making them strategic targets for investment. Additionally, the pipeline acts as a guide to identifying the relevant stakeholders within the organization, enabling more focused discussions and alignment on AI implementation priorities.

Source: Gartner, Generative AI Use Cases for B2B Sales.

GenAI is redefining the future of B2B Sales

Within the next three years, GenAI will emerge as one of the main factors that differentiate the most efficient and financially successful B2B sales organizations. With CROs creating operations teams to scale AI improvements across every phase of the sales process and sales teams using AI to automate reporting and manually-intensive tasks, GenAI is supposed to revamp the time-consuming work that gets in the way of selling.

Gartner’s analysis highlights that AI-driven strategies will soon dominate, with significant gains in efficiency and customer engagement. The message is clear: for sales organizations looking to stay ahead, embracing GenAI is not optional—it’s essential. Those who act now will position themselves as leaders in the evolving world of B2B sales, while those who hesitate risk being left behind.

 

Oct 6

Top ten insights CEOs need to know about GenAI going into 2025

Top ten insights CEOs need to know about GenAI going into 2025

CEOs and C-level executives, including line-of-business leaders managing enterprises, no longer have time for AI hype—they need actionable plans that deliver measurable results.

Every CEO I know has a Gen AI tech trends deck ready for board meetings. They’re all impatient for results.

Gartner’s 2024 Generative AI Planning Survey, published yesterday, reflects how impatient CEOs and their teams are gaining traction with GenAI pilots and AI initiatives. The survey involved 822 business executives from North America, Europe, and Asia/Pacific across eight corporate functions.

Key insights from the GenAI planning survey include the following:

  • 11.3% to 19.7% cost savings are expected from GenAI, with the lowest in finance and highest in marketing and HR, as predicted by CEOs and C-level leaders.

  • 87% of CEOs/C-suite are driving GenAI adoption in areas like sales and finance, pushing top-down initiatives for implementation.

  • Legal departments: 26% rolling out GenAI for contract review in 6 months; already widely used for legal research and analysis.

  • 19.7% cost savings in marketing driven by GenAI, making it the most impacted department for efficiency gains.

  • 28% of leaders cite technical challenges as the top barrier to GenAI implementation, followed by talent acquisition (26%) and costs (24%).

  • 69% of GenAI-advanced companies focus on upskilling staff, while 64% are creating new AI-specific roles to meet talent needs.

Cutting through the hype: What CEOs need to know about GenAI going into next year

Rhetoric into results is the new mantra of the C-suite going into 2025.

That’s especially the case with GenAI.

Board members are worried they’re about to get lapped or, worse, see their companies become gradually irrelevant by competitors who are more focused on making GenAI pay than they are. The greater the acuity and insight of how to turn GenAI into a competitive strength, the greater the speed at which an enterprise executes and gets solid results. Speed isn’t optional anymore, it’s table stakes to compete.

Just as every business needs to keep challenging itself to find new paths to reinvent itself to make AI a competitive strength, the same holds for working professionals. There has never been a better time to double down on new skills and master AI tools, technologies, and knowledge.

The following are ten insights every CEO needs to know about GenAI going into 2025:

  • Over the next 12-18 months, GenAI will boost productivity by 22.6%, outpacing revenue growth at 15.8% and cost savings at 15.2%. While cost efficiency and revenue gains matter, the most immediate and substantial impact will be on operational efficiency. Gartner predicts that enterprises that prioritize GenAI integration will see significant increases in both workflow optimization and financial performance.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • 30% of leaders plan to reduce headcount by 3% to 5% in 2024 due to GenAI-driven automation, with an overall average savings of 4.6%. These reductions will primarily affect roles tied to repetitive or manual tasks as organizations seek to streamline operations. Another 18% anticipate more minor cuts of 1% to 3%, while 14% expect deeper reductions of 8% to 10%, signaling that GenAI’s impact will vary by function. Only 10% foresee no layoffs.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • 87% of sales teams are following CEO or C-suite directives to implement GenAI, demonstrating a top-down strategy that prioritizes AI for revenue growth and a more significant competitive advantage. Supply chain (79%) and finance (74%) also see intense executive pressure, indicating that leadership views AI as critical for optimizing operational efficiency and financial management.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • 84% of organizations prioritize embedding GenAI into existing applications as the top method for enabling their use cases, with 34% making it their first choice. Customizing existing models (74%) and training custom models (65%) follow, while only 59% opt for stand-alone tools. Enterprises are focusing on integrating GenAI within their current systems to drive efficiency and impact rather than relying on isolated or siloed solutions.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • HR leads GenAI budget allocation at 7.1%, followed closely by customer service (7.0%) and finance (6.9%). Across functions, business leaders plan to allocate 5.4% to 7.1% of their 2024 budgets to GenAI initiatives, including spending on technology licensing and employee deployment costs. Gartner observes that this shows a solid commitment to embedding GenAI across departments, with HR and customer service prioritizing it for operational efficiency and innovation.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • 54% of C-level executives prioritize privacy concerns as the top GenAI risk, followed closely by misuse (49%) and job displacement fears (48%). These top concerns highlight the critical need for strong governance and risk management frameworks and plans to ensure ethical, secure AI deployment. CEOs need to step up the pace on this now if they’re going to compete in this dimension of their business in 2025.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • According to 28% of leaders, technical implementation, talent acquisition (26%), and governance issues (25%) are the top three barriers to GenAI adoption. North America struggles more with measuring value (30%), while Europe faces higher cultural resistance (24%). These barriers highlight the need for focused strategies to overcome implementation and talent gaps across regions.

Top ten insights CEOs need to know about GenAI going into 2025

  • 32% of service-centric industries struggle with measuring value from GenAI initiatives, significantly more than asset-centric industries. The top barriers for both include the cost of running AI, technical implementation (32% each), and getting the necessary talent (28%). To excel, enterprises need to address these common challenges and tailor strategies that overcome sector-specific obstacles, including data availability (28% for service-centric industries).

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • Customer service leads GenAI adoption with 40% using real-time speech and text translation, followed by marketing (38% with chatbots and digital humans), sales (34% with generative business intelligence), HR (29% for job descriptions and skills data), supply chain (30% for chatbots and code generation), finance (22% for coding assistance), legal/risk (17% for legal research), and procurement (18% for contract lifecycle management).

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

  • 76% of mature AI organizations actively recruit additional headcount for existing roles to meet GenAI talent needs, significantly more than the 52% of less mature organizations. They also prioritize running AI literacy programs (67%) and upskilling staff with GenAI skills (67%) to ensure their workforce remains competitive. Mature organizations are also more likely to create new roles for GenAI (67%) and establish AI centers of excellence (45%), showing their commitment to both talent acquisition and long-term AI capability development.

Top ten insights CEOs need to know about GenAI going into 2025

Source: Gartner’s 2024 Gartner Generative AI Planning Survey

Sep 17

Top Seven Takeaways from Gartner’s 2024 CIO GenAI Survey

Top Seven Takeaways from Gartner's 2024 CIO GenAI Survey

For 87% of CIOs, generative AI (GenAI) represents more than a technological advancement—it’s a career-defining opportunity.

Gartner’s 2024 CIO Generative AI Survey finds that GenAI is gaining momentum with CIOs, with 95% believing in the technology’s significant potential to improve their organizations. A significant obstacle: a gap between CIOs and their C-suite peers — tempers their optimism.

While CIOs recognize AI’s potential to unleash productivity gains and improve customer experiences, only a fraction of the C-suite sees it as an urgent priority. Closing that gap underscores CIOs’ essential role in championing GenAI by committing to excel at learning every aspect of the new technology and how it can deliver long-term value to their organizations.

The top seven takeaways from Gartner’s survey provide CIOs with a roadmap on how to take a practical, pragmatic approach to bridge the gaps across the C-suite and help their organizations get results from their GenAI strategies.

Strategic Insights from Gartner’s 2024 CIO GenAI Survey

Gartner’s latest CIO survey on GenAI provides insights into how IT leaders can capitalize on the technology’s significant impact, from career growth and expertise development to helping CIOs achieve more support across the C-suite. Each takeaway focuses on how CIOs can leverage AI to drive success for themselves and their organizations.

Here are the survey’s seven most insightful takeaways:

  • More CIOs are starting to view GenAI as a career-enhancing opportunity. Eighty-seven percent of CIOs see GenAI as a pivotal career advancement opportunity, with 44% of those proficient in AI strongly affirming this view. GenAI’s rapid adoption in organizations is proving itself a technology capable of delivering productivity gains and is increasingly becoming a skill and expertise essential for career advancement. For CIOs leading AI initiatives, it’s not just about technology—it’s about positioning themselves as visionary leaders qualified to step into more senior positions. To maximize this opportunity, CIOs need to prioritize the development of AI strategies that demonstrate clear, measurable business outcomes. Continuous learning and certification programs are given to any IT professional, especially CIOs, who want to maintain a competitive edge and have their careers capitalize on GenAI’s growth trajectory.

Source: Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc.

  • CIOs are more focused than ever on increasing their acumen about GenAI. CIOs are rapidly becoming the in-house experts on AI, with 52% now rating themselves as proficient or advanced, up from 38% nine months ago. This growing expertise is crucial, as 67% of CIOs are tasked with leading AI initiatives, often sharing this responsibility with other C-suite members. Gartner recommends that CIOs deepen their AI knowledge further and foster a culture of AI literacy across their teams to capitalize on this trend. Providing targeted training for IT and business leaders to ensure that AI strategies are fully integrated into broader business goals is quickly becoming table stakes.

Source: Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc.

  • Disconnect between CIO optimism and C-suite prioritization. Despite 95% of CIOs believing in the potential for GenAI to deliver value, the survey reveals a disconnect with the C-suite—only 21% of CIOs who consider themselves highly knowledgeable about AI believe their C-suite sees it as a high priority. This gap suggests a need for more effective communication and strategic alignment. CIOs need to focus on translating AI’s potential into language that resonates with the C-suite. Regular briefings and ROI-focused presentations can help bridge this gap and elevate AI as a top priority for all executive leaders.

Source: Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc.

  • CIOs are leading the charge in AI implementations. CIOs are increasingly in charge of GenAI initiatives, with 48% of CIOs responding to the survey indicating that they are the main executives responsible for these initiatives. Another 28% are part of the team responsible for developing AI strategy. This central role places CIOs at the forefront of digital transformation, requiring them to be strategic leaders and hands-on practitioners. CIOs need to establish clear governance frameworks and metrics for AI initiatives to ensure success and alignment with broader organizational goals. Additionally, partnering with other C-suite members, such as the CFO and CMO, can help secure the necessary resources and support for AI projects.


Source: Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc.

  • Focus on productivity gains. GenAI is proving effective in streamlining operations and improving efficiencies organization-wide, with 74% of CIOs citing productivity as its top business value. AI also improves customer experience (49%) and helps streamline digital transformation (31%). These priorities demonstrate AI’s multifaceted role in modern businesses. Gartner recommends that CIOs integrate AI into crucial or core organizational areas, ensuring that AI initiatives align with organizational objectives and are designed to deliver measurable, scalable outcomes.


Source: Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc.

  • Concerns over AI hallucinations. Although GenAI holds great potential, there are significant risks. According to 59% of CIOs, the biggest worry is “hallucinations” or misleading or incorrect outputs. In close succession, 44% and 48% of CIOs express concern about privacy violations and false information spread by malicious attackers. These dangers highlight the importance of solid governance, ongoing oversight, and continued investments in cybersecurity. According to Gartner, CIOs need to prioritize creating AI ethics guidelines and investing in auditing tools. Gartner also notes that reducing these risks will require cultivating a culture of accountability and transparency.


Source: Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc.

  • C-Suite engagement in AI is growing but still lags. The survey shows that while C-suite engagement with AI is growing, 42% of CIOs note increased investment in understanding AI, and 53% still consider their peers novices, highlighting a critical need for further education and alignment. CIOs need to take the lead and champion targeted AI education and strategy sessions to close this gap, ensuring AI initiatives are fully supported and integrated into the organization’s strategic goals.

Conclusion

In Gartner’s 2024 CIO Generative AI Survey, GenAI is more than a technological advancement—it’s a strategic imperative for CIOs seeking business transformation and career advancement. GenAI is rapidly becoming a cornerstone of modern enterprise strategy, with 87% of CIOs seeing it as a career-enhancing tool and 95% as a business value driver.

With only 21% of CIOs seeing AI as a high priority for their executive peers, the journey is difficult. 74% of CIOs are focused on productivity gains, but the C-suite is cautious. CIOs must gain AI expertise and lead the way in aligning AI initiatives with organizational goals to mitigate risks like AI hallucinations through robust governance. CIOs can use GenAI to achieve business success and career growth by strategically navigating these dynamics to cement their role as digital visionaries.

Bibliography:

Struckman, C. (2024). Key findings from the 2024 Gartner CIO generative AI survey (ID G00820936). Gartner, Inc. https://www.gartner.com/document/820936  (Client access required).

Mar 24

BCG Shares Their Insights On What Sets GenAI’s Top Performers Apart

BCG Shares Their Insights On What Sets GenAI's Top Performers Apart

image created in DALL-E

The top 10% of enterprises have one or more GenAI applications in production at scale across their organizations. 44% of these top-performing organizations are realizing significant value from scaled predictive AI cases. 70% of top performers explicitly tailor their GenAI projects to create measurable value.

Boston Consulting Group (BCG) estimates that an organization with $20 billion in revenue can achieve gains of $500 million to $1 billion in profit using GenAI, with nearly a third of those gains coming in the first 18 months. Their recent analysis of what sets GenAI’s top performers apart, What GenAI’s Top Performers Do Differently, looks at the factors that most differentiate enterprises excelling with GenAI today.

What further differentiates these top performers from others is how they’re looking to use GenAI to redefine the functional areas of their organizations. They’re far more likely to have a solid foundation in predictive AI and four times more likely to increase their investment in AI and digital-first strategies and technologies.

Half of the enterprise leaders BCG interviewed say their organizations are testing GenAI in pilot projects today but have not achieved full-scale implementation. The remaining 40% haven’t taken any action on GenAI yet.

BCG Shares Their Insights On What Sets GenAI's Top Performers Apart

Source: Boston Consulting Group, What GenAI’s Top Performers Do Differently.

What Sets The Top 10% Apart

Two-thirds of GenAI’s top-performing enterprises aren’t digital natives like Amazon or Google but instead leaders in biopharma, energy, and insurance. BCG found that a U.S.-based energy company launched a GenAI-driven conversational platform to assist frontline technicians, increasing productivity by 7%. A biopharma company is reimagining its R&D function with GenAI and reducing drug discovery timelines by 25%.

Top GenAI performers have their greatest lead over peers across five main capabilities. These capabilities include having a clear link to business performance, modern technology infrastructure, strong data capabilities, leadership support, and a grounding in responsible AI. The steep curves shown in the graphic below suggest how these five most differentiated capabilities are essential for successful GenAI adoption at scale.

BCG Shares Their Insights On What Sets GenAI's Top Performers Apart

Source: Boston Consulting Group, What GenAI’s Top Performers Do Differently.

Key takeaways from BCG’s analysis of GenAI top performers 

Top performers excel at creating strong links between GenAI initiatives and business value. Seven in ten enterprises who are high achievers know how to build a business case for their GenAI projects and pilots. They’re focused on measuring results and quantifying value. BCG found that in a typical GenAI portfolio, 60% of the initiatives are focused on reducing costs and 40% on increasing revenue.

An all-in mindset when it comes to maintaining and growing a modern technology infrastructure. GenAI top-performing enterprises are three times more likely to already have a modular, modern IT tech stack and supporting infrastructure in place. They’re focused on being prepared to develop new, GenAI-powered services on their current and future AI models while supporting DevOps. BCG says top performers are 1.5 times more likely to focus on building the GenAI stack internally over the coming three years, underscoring their desire to make the technology a core capability for the organizations.

Are pursuing and advanced data strategy that includes unstructured data. GenAI top performers are two times more likely to have data pipelines and data management practices in place to streamline data sourcing and storage. They’re also more likely to have unstructured data expertise. BCG observes that an advanced data strategy “is a critical element of GenAI, given that models are only as strong as the data on which they’re trained.”  Organizations have found success with less mature skills in these areas, although it may take longer as they need to address infrastructure and data strategy gaps or shortcomings.

Strong leadership support for innovation, including the willingness to champion GenAI. Senior executives’ support and prioritizing an innovative culture are the most differentiating factors in defining GenAI’s high performers. Gen AI high performers who are scaling use cases are three times more likely than no-action companies to have leaders who prioritize innovation and actively support GenAI. BCG notes that these leaders often have a deep understanding of the technology’s potential impact on their industry, and they are publicly committed to ensuring that the organization capitalizes on it in new ways that generate value. “Visible support and commitment from our leadership team has been crucial, as it provided the freedom to experiment and deal with failures along the way,” said the head of data and analytics at a global media company referenced in BCG’s report.

Have responsible AI guidelines, guardrails and processes in place. Top-performing enterprises are more likely to have responsible AI frameworks, guidelines, and guardrails in place. BCG observes that a common trait top-performing enterprises have is ensuring their AI systems and workflows put humans in the loop and use only factual data. “Our research shows that leading companies are far more likely to have developed guardrails, guidelines, and policies to ensure that they follow the principles of responsible AI. In the findings, the share of scaling companies that are cautious about the potential misuse of GenAI and taking proactive measures to address these risks is 20 percentage points higher than the share of companies taking no action in this area,” write BCG’s researchers.

Feb 17

IT And Marketing Show Strongest Interest In Adopting Gen AI First

IT, Marketing Show Strongest Interest In Adopting Gen AI First

  • Currently, 16% of organizations have implemented generative AI in production, while 44% are piloting it for potential applications.
  • Interest in deploying generative AI for production applications saw a fivefold increase from the first to the fourth quarter of 2023.
  • Healthcare, manufacturing, and education are the three industries most actively pursuing generative AI adoption.
  • A majority of organizations, 63%, deem CRM data critical to their generative AI initiatives.

These and many other insights are from Dresner Advisory Services‘ recent Generative AI Report. The advisory firm surveyed its research community of over 8,000 organizations and vendors’ customer communities. The study is global in scope, with 50% of respondents from North America, 26% from EMEA, 19% from Asia/Pacific and 6% from Latin America. Dresner’s report stands out for its in-depth and nuanced analysis of gen AI adoption across global organizations.

News about generative AI has captivated technology leaders. Demand for gen AI-related news and insights dominates many organization leaders’ time. 29% are following gen AI news updates constantly, and 30% say they often check in and see what’s new in gen AI, 24% regularly check the news. Overall, 72% of analytics and business intelligence (BI) professionals have made gen AI news a priority. North American respondents are the most diligent with constantly checking gen AI news, reflecting the region having the highest production use of gen AI.

Key takeaways from the report include the following:

Professionals in IT and marketing report plans to be the first adopters of generative AI, with 44% of IT and 36% of marketing professionals saying adopting gen AI is a primary focus. Operations/ production, sales, and C-level executives also show significant interest in adopting gen AI early. Dresner’s report states that “finance and human resources least often indicate overall interest, exceeding a majority only when aggregating their primary, secondary, and tertiary responses.”

gen ai

63% of organizations consider CRM data as critical or very important to generative AI. Finance and accounting data is considered the next most important, followed by call center and supply chain data. Dresner’s analysis found that respondents least often expect generative AI to leverage workforce (HR) data. Organizations are wary of using HR data due to privacy concerns combined with the stringent standards and safeguards on data security and its use across regulated industries today.

gen ai

Gen AI adoption across organizations accelerated rapidly in 2023. From 1Q23 to 4Q23, production use increased nearly fivefold, experimenting increased by 70%, and planned use in 12 months increased by 157%. Dresner’s research results reflect a major shift in generative AI prioritization last year. The report’s authors contend that implementation activity and funding were primarily from autonomous, decentralized sources, not from C-level mandates or sponsors, as it occurred late in fiscal years and into annual budget cycles.

gen ai

Consumer services lead gen AI production levels at 43%. Technology, business services, and healthcare have the next three highest levels of gen AI production in use today. The education industry reports the highest experimentation rate at 67%, closely followed by healthcare at 62%, while government trails at 50%. The report notes that the government also reports the highest levels for planned use beyond 12 months and no planned use.

gen ai

40% of organizations consider it critical to achieve productivity and efficiency gains from gen AI. One in three (30%) say improving customer experience and personalization is the next most critical priority, followed by improved search quality and decision-making (26%).

gen ai

Data privacy concerns are considered critical to 46% of organizations pursuing gen AI initiatives today. Legal and regulatory compliance, the potential for unintended consequences, and ethics and bias concerns are also significant. Less than half of respondents—46% and 43%, respectively—consider costs and organizational policy important to generative AI adoption.

gen ai

 

Feb 11

Top 10 Insights From Forrester’s State of Generative AI in 2024 Report

Top 10 Insights From Forrester's State of Generative AI in 2024 Report

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Over 90% of enterprise AI decision-makers have concrete plans to adopt generative AI (gen AI) for internal and customer-facing use cases. Nearly half, 47%, say productivity gains are the primary goal. Those anticipated gains are closely followed by greater innovation (44%) and cost efficiency (41%). One in three, or 34%, expect AI to deliver greater revenue growth.

Productivity gains are happening faster than enterprises can track because Shadow AI is growing quicker than many IT and security teams anticipated. OpenAI says their enterprise adoption is soaring, with over 80% of Fortune 500 companies’ workers and departments having accounts.

Enterprise workers are achieving a 40% performance boost thanks to ChatGPT based on a recent Harvard study. A second study from MIT discovered that ChatGPT reduced skill inequalities and accelerated document creation times while enabling enterprise workers to be more efficient with their time. Seventy percent haven’t told their bosses about it.

Forrester: A Wave Of Disruption Is Coming

Forrester’s recent report, The State of Generative AI, 2024, warns enterprises not to discount the impact of generative AI on their operations and to start planning for greater experimentation, governance, and security now.

Get ready for the challenges of defining and managing bring your own AI (BYOAI) as workers are inventing and adopting gen AI tools and apps faster than IT or security can keep up. Forrester advises that enterprises need to have forward-thinking governance and security guardrails in place before launching their AI-based apps.

With nearly every enterprise app and platform integrating gen AI into its feature set, it’s up to IT, security, and senior management to have an AI plan that can adapt and flex fast to the fast-growing feature set gen AI is delivering.

Enterprise AI leaders also need to define where they stand on the controversial and complex state of model training data. Forrester says that questions regarding the quality of training data using copyright material, model and data bias, and frequent “hallucinations” by models.

“In 2024, as organizations embrace the generative AI (genAI) imperative, governance and accountability will be a critical component to ensure that AI usage is ethical and does not violate regulatory requirements,” writes Forrester in their cybersecurity predictions late last year. “This will enable organizations to safely transition from experimentation to implementation of new AI-based technologies,” the report continues.

Top 10 Insights From Forrester’s State of Generative AI

The ten most valuable insights from Forrester’s State of Generative AI report provide a comprehensive overview of the current and future landscape of generative AI. Noteworthy for its balance between opportunities and risks, the report explains the hurdles in front of enterprises looking to gain value from gen AI now and in the future.

Here are the top 10 insights from the report:

Gen AI shows strong potential to improve and scale enterprise operations. Forrester is optimistic regarding the potential of gen AI to increase productivity and deliver measurable business value. “Forrester expects that gen AI will add convenience to and remove friction from a variety of experiences, reshape jobs in ways we are only beginning to contemplate and disrupt organizations and industries,” writes Forrester’s research team in the report. The report explains that there are three broad tiers of generative AI suppliers, further supporting the market’s expansion and growth.

Top 10 Insights From Forrester's State of Generative AI in 2024 Report

Source: Forrester, The State of Generative AI, 2024 report. January 26, 2024

 

Large Language Models will continue to dominate the gen AI narrative. Large language models (LLMs), including Anthropic, Google, Meta, and OpenAI’s GPT series, will continue to dominate the gen AI landscape. Forrester notes that significant data and infrastructure requirements make the task of creating and maintaining an LLM difficult for companies considering competing in the market. Open-source LLMs are redefining the market, a point Forrester touches on briefly.

Gen AI is becoming part of planning cycles in enterprises: Forrester found that over 90% of global enterprise AI decision-makers have definite plans to implement generative AI. Internal use cases are dominating the planning cycles of enterprise AI leaders today.

Top 10 Insights From Forrester's State of Generative AI in 2024 Report

Source: Forrester, The State of Generative AI, 2024 report. January 26, 2024

Overcoming technical skills shortages and integration challenges stand in the way of achieving benefits. A third of enterprise AI leaders say that lack of technical skills in their organizations is the single greatest roadblock to their gaining the benefits they’re looking for from gen AI. Twenty-eight percent say they’re having difficulty integrating gen AI into their existing tech stacks and infrastructure. The potential to gain significant benefits from gen AI motivates enterprise AI leaders to look for new ways to overcome technical skills shortages and find new ways to integrate gen AI into their infrastructure.

Top 10 Insights From Forrester's State of Generative AI in 2024 Report

Source: Forrester, The State of Generative AI, 2024 report. January 26, 2024

Ethical and safe gen AI use will require new cybersecurity and governance approaches. Enterprises need to decide how they approach the most challenging and controversial aspects of LLMs, gen AI, and the future of AI at scale in their companies now rather than later. The core message of Forrester’s report is for enterprises not to procrastinate but to start making plans now for their stance on the issues of model bias, data security, regulatory compliance, and ethics of model training.

Weaponized LLMs are a fact of life for every enterprise looking to adopt these technologies today. There’s also the growing threat of intellectual property and confidential data being accidentally shared with LLMs via ChatGPT and comparable chatbots. The intensity cybersecurity providers are putting behind this problem makes it one of the fastest evolving areas in the industry today.

While not mentioned by Forrester in their report, these vendors are defining the state of the art when it comes to protecting confidential data being entered into LLMs. Cisco, Ericom Security by Cradlepoint’s Generative AI isolation, Menlo Security, Nightfall AI,  Wiz, and Zscaler have all developed and launched solutions to reduce the threat of confidential data making it into LLMs via chatbots.

The use of a virtual browser that is separate from an organization’s network environment in the Ericom Cloud distinguishes Ericom’s Generative AI Isolation. Data loss protection, sharing, and access policy controls are applied in the cloud to prevent confidential data, PII, or other sensitive information from being submitted to the LLM and potentially exposed.

“Generative AI websites provide unparalleled productivity enhancements, but organizations must be proactive in addressing the associated risks,” said Gerry Grealish, Vice President of Marketing Ericom Cybersecurity Unit of Cradlepoint. “Our Generative AI Isolation solution empowers businesses to attain the perfect balance, harnessing the potential of generative AI while safeguarding against data loss, malware threats, and legal and compliance challenges.”

Early adopters are implementing gen AI in a wide variety of use cases, ranging from operations to customer engagement and product development. Forrester notes that they’re seeing organizations use knowledge management bots to accelerate workflows, automate tasks, generate new ideas, and drive innovation across a broad base of use cases. Early adopters are also piloting gen AI for diverse use cases across operations, customer engagement, and product development. Forester emphasizes that for external use cases, they’re seeing enterprises adopt a main-in-the-middle workflow to strengthen model training with human intelligence – and avert potential errors in model response.

Top 10 Insights From Forrester's State of Generative AI in 2024 Report

Source: Forrester, The State of Generative AI, 2024 report. January 26, 2024

Internal use cases precede external use cases as enterprises look to gain expertise in controlled environments. Companies will initially focus on internal use cases for generative AI to refine their models before slowly expanding to customer-facing applications, employing heavy human-in-the-loop management. Forrester is seeing gen AI being used internally to drive employee productivity and workflow optimization gains first. The top three use cases of employee productivity, knowledge management, and software development are all focused on internal improvements.

Legal and intellectual property uncertainty will continue to surround gen AI. Forrester implies there’s going to be an increasingly complex, controversial legal landscape regarding the data models are trained on, especially when it comes to copyrighted content.

Privacy and regulatory concerns are going to continue influencing adoption. Forrester is seeing enterprises in heavily regulated industries exercising extreme caution to protect company and customer data, with some even banning tools like ChatGPT over concerns about data protection and regulatory backlash.

Enterprises need to get a sense of urgency about preparing for gen AI governance and experimentation. Having a clear vision of how they’re going to adopt gen AI is essential if enterprises are going to succeed in governing these new technologies at scale. The combination of growing and recruiting in-house skills, having a solid plan for BYOAI, and defining guardrails for internal use cases are all needed to avoid being blindsided by risks.