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Posts tagged ‘Artificial Intelligence (AI)’

Gartner Predicts AI Software Will Grow To $297 Billion By 2027

Gartner Predicts AI Software Will Grow To $297 Billion By 2027

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Predicting global spending on AI software will surge from $124 billion in 2022 to $297 billion in 2027, Gartner forecasts the market will grow at a 19.1% compound annual growth rate in the next six years.

Generative AI (GenAI) software spending is expected to skyrocket from 8% in 2023 to 35% by 2027. GenAI’s rapid growth is attributed to enterprise software vendors integrating AI tools into current and future releases, streamlining the widespread adoption of GenAI-based features and new apps, emerging as the fastest-growing category of AI software.

Gartner predicts the integration of AI tools will be most prevalent in marketing, product design, and customer service, reflecting a shift towards more personalized and efficient operations. The research firm provides an extensive analysis of AI software’s growth areas and opportunities in their recently published report, Forecast Analysis: Artificial Intelligence Software, 2023-2027, Worldwide (client access required). The forecast is based on over 500 AI use cases sourced from Gartner’s AI use case prisms and related research.

What Driving The AI Market Boom?

Key assumptions that are driving the forecast include the prediction that greater than 70% of independent software vendors (ISVs) will have embedded GenAI capabilities in their enterprise applications by 2026, a major jump from fewer than 1% today.

Thirty-nine percent of worldwide organizations will be in the experimentation phase of Gartner’s AI adoption curve by 2025, with 14% being in the expansion phase. Gartner predicts that by 2027, 36% of organizations in the experimentation phase will also start to adopt use cases with high business value but low time-to-financial impact (TOFI).

Another factor driving long-term market growth is how spending on AI software increases with organizational maturity. Gartner notes that organizational maturity is lower today versus the higher hype levels and market interest in AI technologies. As organizations gain greater maturity with AI experimentation, spending will increase.

Gartner Predicts AI Software Will Grow To $297 Billion By 2027

Source: Gartner, Forecast Analysis: Artificial Intelligence Software, 2023-2027, Worldwide

“We expect to see ongoing demand for more AI enhancements within software applications and more opportunities for providers to deliver software to build AI. However, do not expect these markets to become saturated (where supply outstrips demand) during the forecast period,” Gartner’s analysts write in the forecast analysis.

Application areas growing the fastest

Gartner predicts AI spending on financial management system (FMS) components will be the largest application market overall. FMS supports the office of finance with capabilities for forecasting, planning, cash application and collections, balance reconciliation, and others.

FMS vendors are doubling down on AI already to provide proven productivity and optimization support, integrating AI-based features in their apps and platforms. AI’s inherent advantages quickly lead to quantified performance and productivity gains with FMS systems, which are table stakes for building a solid business case for potential customers.

Digital commerce applications are the highest-growth AI application market. Digital commerce applications are designed to streamline commerce operations and related areas, including optimization, customer segmentation, image categorization, and others. Gartner defines the AI capabilities in digital commerce to include personalization, automated execution, and content generation.

Gartner Predicts AI Software Will Grow To $297 Billion By 2027

Source: Gartner, Forecast Analysis: Artificial Intelligence Software, 2023-2027, Worldwide

Predicting Generative AI’s Growth

Gartner is predicting that GenAI will eventually become a cornerstone of all AI software spending, reaching 35% of worldwide revenues by 2027.

The report’s authors point to the proliferation of AI copilots being integrated into a wide variety of enterprise systems as a primary catalyst driving this area of the market’s growth. Copilot systems are in use today within email systems, customer support chatbots, and a wide variety of marketing applications, with content creation and personalization vendors fast-tracking copilots into their apps and platforms.

One of the many data points that support the optimistic growth forecast for GenAI is Microsoft’s success with their Microsoft Dynamics 365 Copilot, launched in March of last year. Since then, more than 130,000 organizations have experienced copilot capabilities in Microsoft Dynamics 365 and Microsoft Power Platform.

Gartner Predicts AI Software Will Grow To $297 Billion By 2027

Source: Gartner, Forecast Analysis: Artificial Intelligence Software, 2023-2027, Worldwide

Large Language Models (LLMs) are the growth catalyst natural language platforms need

Gartner is predicting that the data science and AI platform market will see the greatest amount of software spending in the forecast period. They’ve defined the market as including machine learning (ML) platforms and cloud AI developer services. “The data science and AI platforms market is accelerated by the growth of AI and the democratization of technology, where capabilities like ease of use, workflow, collaboration, and deployment provide support for citizen data scientists,” writes Gartner’s analysts in the report.

The leading AI platforms seeing the greatest growth are natural language technologies (which include LLMs), data science and AI platforms, computer vision platforms, and analytics and BI platforms. LLMs will be the fuel that keeps natural language technology-based platforms growing for the next three years. They’re the emerging workhouses of the AI software market.

Gartner Predicts AI Software Will Grow To $297 Billion By 2027

Source: Gartner, Forecast Analysis: Artificial Intelligence Software, 2023-2027, Worldwide

 

Machine Learning Engineer Is The Best Job In The U.S. According To Indeed

  • Machine Learning Engineer job openings grew 344% between 2015 to 2018, and have an average base salary of $146,085.
  • At $158,303, Computer Vision Engineers earn among the highest salaries in tech
  • The average base salary of the 25 best jobs in the U.S. according to Indeed is $104,825, and the median base salary is $99,007.
  • Agile Coach is the highest paying job with an average base salary of $161,377.
  • 9 of the top 25 jobs in the U.S. this year are in tech fields according to Indeed.
  • Five jobs are heavily dependent on applicants’ Artificial Intelligence (AI) skills and expertise.

These and many other insights are from this Indeed’s The Best Jobs in the U.S.: 2019 study released this week. Indeed defined the best jobs as those experiencing the fastest growth measured by the increase in job postings between 2015 and 2018, in conjunction with those offering the highest pay using a baseline salary of $75,000. Indeed’s best jobs of 2019’s data set is available here in Microsoft Excel.

Key insights from Indeed’s ranking of the best jobs of 2019 include the following:

  • At $158,303, Computer Vision Engineers earn among the highest salaries in tech according to Indeed, followed Machine Learning Engineers with a base salary of $146,085. The average base pay of the nine tech-related jobs that made Indeed’s list is $122,761, above the median salary of $99,007 for the entire group of the top 25 jobs. Indeed’s top 25 jobs for 2019 are illustrated below in descending salary order with the median salary providing a benchmark across the group. Please click on the graphic to expand for easier reading.

  • Three of the top 10 fastest growing jobs as measured by percentage growth in the number of job postings are in tech. From 2015 to 2018, job postings for Machine Learning Engineers grew 344%, followed by Full-stack developers (206%) and Salesforce developers (129%). In aggregate, all nine technology-related job postings increased by 146% between 2015 and 2018. The graphic below illustrates the percentage of growth in the number of postings between 2015 and 2018. Please click on the graphic to expand for easier reading.

  • Comparing average base salary to percentage growth in job postings underscores the exceptionally high demand for Machine Learning Engineers in 2019. Technical professionals with machine learning expertise today are in an excellent position to bargain for the average base salary of at least $146,085 or more. Full-stack developers and Salesforce developers are in such high demand, technical professionals with skills on these areas combined with experience can command a higher salary than the average base salary. The following graphic compares the average base salary to percentage growth in job postings for the years 2015 – 2018. Please click on the graphic to expand for easier reading.