While CIOs are experiementing with LLMs and AI Agents, finding genAI ROI is challenging. Recent reports from AWS, MIT, and Workday highlight the problem and what changes CIOs must lead to deliver business value.

Leaders know there’s a lot of hype around genAI. Gartner placed generative AI into its trough of disillusionment one year ago. GenAI hasn’t hit the bottom yet in Gartner’s Hype Cycle for AI in 2025. But buying sentiments are clearly changing from one of irrational exuberance to pragmatic experimentation.  

The problem for CIOs is that much of their experimentation isn’t getting into production or creating genAI ROI. It’s going to be challenging for CIOs to fuel investment with productivity as the only driver . CIOs who only focus on efficiencies may find that AI is the end of IT as they know it.

Three of my recommendations on delivering value from genAI

Promising AI use cases for genAI ROI in CX and the future of work that have top and bottom-line impacts. I’ve also shared best practices in architecture, software engineering, and AI agent governance.

My question today is, how should CIOs assess their AI programs? What areas target high business value, accelerate paths to production, and engage employees in enthusiastic collaboration?

I’ve been reviewing the research to develop my thesis on what CIOs must lead to drive genAI ROI.

• C-level ownership is the wrong question and should focus on bottom-up organizational programs. Examples: lead change management, experiment that leads to lifelong learning on AI, and redefinine roles for the genAI era.
• Productivity and efficiencies are insufficient ROI targets. CIOs must find growth opportunities, customer experience differentiators, and genAI product enhancements.
• Build versus buy is the wrong decision mindset. Focus on partnering and configuring AI agents where there’s a scale of operations and high-quality data.

Three recent reports support my thesis, and I selected 10 data points that everyone should review.

Organizational dysfunction is dampening genAI’s impacts

From the AWS Study Generative AI Adoption Index:

• While 90% of organizations now deploy generative AI tools, 44% have advanced beyond early testing to production deployment.
• Organizations are rapidly consolidating AI leadership, with 60% already having appointed CAIOs (Chief AI Officers) and another 26% planning appointments by 2026.
• Today, just 14% of organizations have a change management strategy, but this will increase to 76% by the end of 2026, highlighting growing recognition of the need for structured adaptation.

One of the report’s recommendations: “The ideal [change management] strategy should address operating model changes, data management practices, talent pipelines, and scaling strategies among a range of other dynamic factors associated with generative AI adoption.”

My take: Look for my follow-up article on why promoting a CAIO is the wrong solution. I’m shocked that  60% of organizations have one, while only 14% have AI change management strategies. Recall my #1 reason why digital transformations fail, a problem also pertinent to AI programs.

Partner on solutions for front-office workflows

From MIT’s State of AI in Business 2025:

• Despite $30–40 billion in enterprise investment into GenAI, this report uncovers a surprising result in that 95% of organizations are getting zero return. Just 5% of integrated AI pilots are extracting millions in value, while the vast majority remain stuck with no measurable P&L impact.
• Only 5% of enterprises have AI tools integrated in workflows at scale, and 7 of 9 sectors show no real structural change.
• Strategic partnerships are twice as likely to succeed as internal builds. External partnerships with learning-capable and customized tools, including buying external tools and co-developing with vendors, reached deployment ~67% of the time, compared to ~33% for internally built tools.
• Front-office wins include 40% faster lead qualification speed and 10% improved customer retention through AI-powered follow-ups and messaging.

One of the report’s recommendations: “The standout performers are not those building general-purpose tools, but those embedding themselves inside workflows, adapting to context, and scaling from narrow but high-value footholds.”

My take: Focus dev efforts on the data, workflow, and integrations – and less on the AI. Find partners that can identify configurable AI agents and guide the implementation.

Engage employees on AI’s hype, focus areas, and people benefits

From Workday’s report on AI Agents Are Here—But Don’t Call Them Boss.

• Organizations are swiftly deploying AI agents, and 82% are using them. Despite optimism, a notable 27% of organizations still believe AI agents are overhyped. Concerns exist about a decline in critical thinking (48%) and the erosion of meaningful human interaction (36%).
• Expected benefits include improved employee growth and development (85%), work-life balance (80%), and job satisfaction (79%). But 48% are concerned that AI agents will increase pressure on employees to work faster.
• Respondents highlighted the aspects of workforce management that will benefit the most from AI agent adoption: Forecasting and planning (84%), scheduling and labor optimization (80%), and time and attendance (75%). Trust dwindles when AI makes critical financial decisions (only 40% are comfortable) or operates in the background without human knowledge (just 24% are comfortable).

One of the report’s recommendations: “Even as familiarity with agents increases optimism, building trust in AI extends beyond mere technology implementation. It necessitates effective change management and fostering a secure, informed, and empowered environment for employees to engage with agentic AI.”

My take: Employees see the headlines of job cuts and hiring freezes. The C-Suite should expect it to become even more challenging to engage subject matter experts on the knowledge to train AI agents and employees on using them. If your AI initiatives lack a compelling vision statement, then you’re leaving it to employees to guess at the objectives, business benefits, and what’s in it for them.

Advice for CIOs on genAI ROI

So again, here are my recommendations. CIOs should focus on

• Championing organizational programs in change management, learning, and role definition
• Targeting growth opportunities, customer experience differentiators, and genAI product enhancements
• Partnering on AI agents where there’s a scale of operations and high-quality data

 At StarCIO, we deliver center of excellence programs that focus on developing leaders and transformational best practices tailored to the organization’s goals, culture, and staffing. Our approach includes a mix of leadership, learning, and advisory programs that guide teams on developing standards, cultural principles, AI innovations, and excellence with technology platforms. Reach out to StarCIO to learn more about our programs.