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GenAI Inspiring Greater Enterprise Adoption of Other AI Types

The rapid rise of creative "right-brain" generative AI (GenAI) has opened the door to greater adoption of the more analytical "left-brain" AI decisioning solutions by global businesses, according to new research from Pegasystems. 

The study, conducted by research firm Savanta, found 95% of respondents felt the increased prevalence of GenAI was directly responsible for their adoption of other types of AI tools, with one third saying it played a major role in their decision. It also showed generative AI has become the predominant way of deploying artificial intelligence (AI) within global enterprises, highlighting the extent to which it has been embraced as both a productivity enhancer and a creative partner for innovation. 

The study explored how business decision makers are implementing AI through the lens of the two sides of the human brain: the more rational, analytical AI decisioning side (left-brain), and the more creative, generative side (right-brain). It found that right-brain generative AI is the most used AI within enterprises today, with two in five respondents (44%) saying they use it mostly for creative or productivity-enhancing tasks such as content creation (61%), curating large stores of information (54%), or in conversational chatbots (51%). Conversely, less than a third of all respondents (30%) predominantly use rational left-brain AI decisioning solutions, such as predictive analytics (57%), or decision management tools (42%). Only 25% of respondents use an equal number of both left and right brain AI tools. Other findings from the research include:

AI spend is on the rise…but so are transformational expectations

92% of respondents say it's likely they will increase their use of AI in the next five years, with 74% saying they are either extremely or very confident AI can add transformational business value to their organization over the next five to 10 years. In the short-term, the vast majority (82%) also expect to be able to directly attribute up to half of their increased profits over the next three years to their use of AI. However, 85% say they spend up to half of their annual IT budget on AI solutions. With 77% admitting to at least some level of waste in their budget spend due to a lack of a proper strategy, it's clear that more care is required around how and why these investments are made.

But … businesses overestimate their AI understanding

The vast majority of respondents (93%) say they have a good understanding of AI and the way it works. Despite this, 80% think AI has been in general business use for less than five years — with just 7% saying it has been in use for 10 years or more, despite mainstream usage dating back to the 1980s. Meanwhile, nearly two-thirds (65%) could not correctly identify an accurate definition of generative AI — despite only 3% admitting they don't know what the technology is. These numbers could explain why nearly two-thirds (61%) say they have had a failed AI implementation.

AI trust and the enterprise — it's complicated

: Half of respondents (47%) are concerned with resting the success of their brand on AI, while 51% also admit they have concerns over AI transparency and bias. 42% are also worried about AI taking their jobs, while 40% are concerned about the potential enslavement of humanity by AI-powered robots. Despite these concerns, a majority (62%) have some level of trust in AI's ability to completely run a department if they felt it would improve overall results. Meanwhile, 41% of respondents prefer to trust a human to build customer relationships, provided they had assistance from AI — compared to just 15% who trust a human more without AI intervention.

Demand for AI skills is growing

Two in ten (20%) think their organization has weak AI skills and experience, while more than one quarter (28%) say this presents a barrier to further AI use within their business. However, 98% find prior AI skills and experience valuable when considering new applicants to join their team, suggesting a growing importance of fostering an AI-literate workforce. Those with hands-on AI experience such as prompt engineering are most in demand (64%), followed by experts in AI theory and academics on the subject (46%). Just 5% are not proactively looking to hire anyone based on their AI skills or experience. 

"Generative AI is the flag-bearer of a new wave of AI enthusiasm, so it's no surprise that so many businesses are using it as a catalyst to not only explore other types of AI but also to drive more creativity and innovation," said Don Schuerman, CTO, Pega. "The next few years are going to see continued growth, not only in the acceleration of artificial intelligence in all its various forms, but also in terms of its adoption. To make the most of this, organizations must ensure they have the requisite skills, expertise, and understanding to make their AI projects a success. In the coming years, we expect to see more and more businesses not just adopting AI productivity tools, but partnering with AI to drive innovations that produce the best possible outcomes for themselves and their customers." 

Methodology: Pega surveyed more than 500 business decision makers worldwide on their views, understanding, and plans for implementing AI solutions, as well as the challenges and opportunities they see in the technology. The results included responses from North America, the United Kingdom, France, Australia, and Germany.

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GenAI Inspiring Greater Enterprise Adoption of Other AI Types

The rapid rise of creative "right-brain" generative AI (GenAI) has opened the door to greater adoption of the more analytical "left-brain" AI decisioning solutions by global businesses, according to new research from Pegasystems. 

The study, conducted by research firm Savanta, found 95% of respondents felt the increased prevalence of GenAI was directly responsible for their adoption of other types of AI tools, with one third saying it played a major role in their decision. It also showed generative AI has become the predominant way of deploying artificial intelligence (AI) within global enterprises, highlighting the extent to which it has been embraced as both a productivity enhancer and a creative partner for innovation. 

The study explored how business decision makers are implementing AI through the lens of the two sides of the human brain: the more rational, analytical AI decisioning side (left-brain), and the more creative, generative side (right-brain). It found that right-brain generative AI is the most used AI within enterprises today, with two in five respondents (44%) saying they use it mostly for creative or productivity-enhancing tasks such as content creation (61%), curating large stores of information (54%), or in conversational chatbots (51%). Conversely, less than a third of all respondents (30%) predominantly use rational left-brain AI decisioning solutions, such as predictive analytics (57%), or decision management tools (42%). Only 25% of respondents use an equal number of both left and right brain AI tools. Other findings from the research include:

AI spend is on the rise…but so are transformational expectations

92% of respondents say it's likely they will increase their use of AI in the next five years, with 74% saying they are either extremely or very confident AI can add transformational business value to their organization over the next five to 10 years. In the short-term, the vast majority (82%) also expect to be able to directly attribute up to half of their increased profits over the next three years to their use of AI. However, 85% say they spend up to half of their annual IT budget on AI solutions. With 77% admitting to at least some level of waste in their budget spend due to a lack of a proper strategy, it's clear that more care is required around how and why these investments are made.

But … businesses overestimate their AI understanding

The vast majority of respondents (93%) say they have a good understanding of AI and the way it works. Despite this, 80% think AI has been in general business use for less than five years — with just 7% saying it has been in use for 10 years or more, despite mainstream usage dating back to the 1980s. Meanwhile, nearly two-thirds (65%) could not correctly identify an accurate definition of generative AI — despite only 3% admitting they don't know what the technology is. These numbers could explain why nearly two-thirds (61%) say they have had a failed AI implementation.

AI trust and the enterprise — it's complicated

: Half of respondents (47%) are concerned with resting the success of their brand on AI, while 51% also admit they have concerns over AI transparency and bias. 42% are also worried about AI taking their jobs, while 40% are concerned about the potential enslavement of humanity by AI-powered robots. Despite these concerns, a majority (62%) have some level of trust in AI's ability to completely run a department if they felt it would improve overall results. Meanwhile, 41% of respondents prefer to trust a human to build customer relationships, provided they had assistance from AI — compared to just 15% who trust a human more without AI intervention.

Demand for AI skills is growing

Two in ten (20%) think their organization has weak AI skills and experience, while more than one quarter (28%) say this presents a barrier to further AI use within their business. However, 98% find prior AI skills and experience valuable when considering new applicants to join their team, suggesting a growing importance of fostering an AI-literate workforce. Those with hands-on AI experience such as prompt engineering are most in demand (64%), followed by experts in AI theory and academics on the subject (46%). Just 5% are not proactively looking to hire anyone based on their AI skills or experience. 

"Generative AI is the flag-bearer of a new wave of AI enthusiasm, so it's no surprise that so many businesses are using it as a catalyst to not only explore other types of AI but also to drive more creativity and innovation," said Don Schuerman, CTO, Pega. "The next few years are going to see continued growth, not only in the acceleration of artificial intelligence in all its various forms, but also in terms of its adoption. To make the most of this, organizations must ensure they have the requisite skills, expertise, and understanding to make their AI projects a success. In the coming years, we expect to see more and more businesses not just adopting AI productivity tools, but partnering with AI to drive innovations that produce the best possible outcomes for themselves and their customers." 

Methodology: Pega surveyed more than 500 business decision makers worldwide on their views, understanding, and plans for implementing AI solutions, as well as the challenges and opportunities they see in the technology. The results included responses from North America, the United Kingdom, France, Australia, and Germany.

Hot Topics

The Latest

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...