AI Appreciation Day Feature: Businesses View AI Agents as Essential, Not Just Experimental

Learn more about IBM

A new study by the IBM Institute for Business Value reveals that enterprises are expected to significantly scale AI-enabled workflows, many driven by agentic AI, relying on them for improved decision making and automation.

The AI Projects to Profits study revealed that respondents expect AI-enabled workflows to grow from 3% today to 25% by the end of 2025. With 70% of surveyed executives indicating that agentic AI is important to their organization's future, the research suggests that many organizations are actively encouraging experimentation.

As the pace of digital transformation accelerates, enterprises can turn to AI agents as the next evolution of intelligent automation. 83% of respondents say they expect AI agents to improve process efficiency and output by 2026, and 71% believe agents will autonomously adapt to changing workflows.

"We see more clients looking at agentic AI as the key to help them move past incremental productivity gains and actually gain business value from AI, especially when applied in their core processes like supply chain and HR," said Francesco Brenna, VP & Senior Partner, AI Integration Services, IBM Consulting. "This isn't about plugging an agent into an existing process and hoping for the best. It means re-architecting how the process is executed, redesigning the user experience, orchestrating agents end-to-end, and integrating the right data to provide context, memory, and intelligence throughout."

These are the top five benefits of agentic AI systems that are driving adoption across industries, according to the report:

1. Over two-thirds (69%) of executives surveyed say "improved decision-making" is the number one benefit of agentic AI systems.

2. 67% of those surveyed cite "cost reduction through automation" as a benefit.

3. Almost half (47%) of leaders surveyed indicate "competitive advantage" as a top benefit of agentic AI systems.

4. "Scaled employee experience" is cited as a top benefit, according to 44% of executives surveyed.

5. 42% of those surveyed indicate that "improved talent retention" is another major benefit to implementing agentic AI systems.

Though benefits were cited among those surveyed, concerns with agentic AI adoption are still present among leaders. Those surveyed indicate that concerns around data (49%), trust issues (46%) and skills shortages (42%) remain barriers to adoption for their organizations.

Other key findings include:

  • Executives surveyed indicate that AI investment has grown to about 12% of IT spend in 2024. By 2026, the participants indicated they expect this number is to increase by over two-thirds to account for 20% of IT spend.
  • Respondents say that 64% of AI budgets are now spent on core business functions, underscoring AI's move from an experimentation phase to an important part of business strategy.
  • The proportion of surveyed organizations relying on an ad hoc approach to AI has declined from a reported 19% last year to just 6% today, indicating increased confidence and commitment to AI-driven transformation.
  • One in four companies surveyed are already using an "AI-first" approach. Among those with an AI-first approach, respondents say they attribute more than half of their revenue growth (52%) and operating margin improvements (54%) to AI initiatives in the last 12 months

Methodology: The IBM Institute for Business Value study, in partnership with Oxford Economics, draws insights from two 2025 surveys: the "AI at the core survey" (2,500 executives across 18 industries and 19 regions) and the "Agentic AI pulse survey" (400 C-suite executives across 15 roles, 11 industries, and 6 countries). Survey questions explored AI's current role in business operations, including its impact on revenue, profitability, productivity, and resource efficiency. Further analysis was conducted to identify key relationships, trends and associations within the dataset.

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AI Appreciation Day Feature: Businesses View AI Agents as Essential, Not Just Experimental

Learn more about IBM

A new study by the IBM Institute for Business Value reveals that enterprises are expected to significantly scale AI-enabled workflows, many driven by agentic AI, relying on them for improved decision making and automation.

The AI Projects to Profits study revealed that respondents expect AI-enabled workflows to grow from 3% today to 25% by the end of 2025. With 70% of surveyed executives indicating that agentic AI is important to their organization's future, the research suggests that many organizations are actively encouraging experimentation.

As the pace of digital transformation accelerates, enterprises can turn to AI agents as the next evolution of intelligent automation. 83% of respondents say they expect AI agents to improve process efficiency and output by 2026, and 71% believe agents will autonomously adapt to changing workflows.

"We see more clients looking at agentic AI as the key to help them move past incremental productivity gains and actually gain business value from AI, especially when applied in their core processes like supply chain and HR," said Francesco Brenna, VP & Senior Partner, AI Integration Services, IBM Consulting. "This isn't about plugging an agent into an existing process and hoping for the best. It means re-architecting how the process is executed, redesigning the user experience, orchestrating agents end-to-end, and integrating the right data to provide context, memory, and intelligence throughout."

These are the top five benefits of agentic AI systems that are driving adoption across industries, according to the report:

1. Over two-thirds (69%) of executives surveyed say "improved decision-making" is the number one benefit of agentic AI systems.

2. 67% of those surveyed cite "cost reduction through automation" as a benefit.

3. Almost half (47%) of leaders surveyed indicate "competitive advantage" as a top benefit of agentic AI systems.

4. "Scaled employee experience" is cited as a top benefit, according to 44% of executives surveyed.

5. 42% of those surveyed indicate that "improved talent retention" is another major benefit to implementing agentic AI systems.

Though benefits were cited among those surveyed, concerns with agentic AI adoption are still present among leaders. Those surveyed indicate that concerns around data (49%), trust issues (46%) and skills shortages (42%) remain barriers to adoption for their organizations.

Other key findings include:

  • Executives surveyed indicate that AI investment has grown to about 12% of IT spend in 2024. By 2026, the participants indicated they expect this number is to increase by over two-thirds to account for 20% of IT spend.
  • Respondents say that 64% of AI budgets are now spent on core business functions, underscoring AI's move from an experimentation phase to an important part of business strategy.
  • The proportion of surveyed organizations relying on an ad hoc approach to AI has declined from a reported 19% last year to just 6% today, indicating increased confidence and commitment to AI-driven transformation.
  • One in four companies surveyed are already using an "AI-first" approach. Among those with an AI-first approach, respondents say they attribute more than half of their revenue growth (52%) and operating margin improvements (54%) to AI initiatives in the last 12 months

Methodology: The IBM Institute for Business Value study, in partnership with Oxford Economics, draws insights from two 2025 surveys: the "AI at the core survey" (2,500 executives across 18 industries and 19 regions) and the "Agentic AI pulse survey" (400 C-suite executives across 15 roles, 11 industries, and 6 countries). Survey questions explored AI's current role in business operations, including its impact on revenue, profitability, productivity, and resource efficiency. Further analysis was conducted to identify key relationships, trends and associations within the dataset.

Related Links

Hot Topics

The Latest

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Why ITOps Need Right-Sized AI, Not Bigger Models

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

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Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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