I recently shared why CIOs must look beyond productivity drivers and seek genAI opportunities in digital transformation. CFOs sniffing productivity improvements and sold on automation drivers will demand cost savings before the CIO can deliver real transformation opportunities.

I also shared five IT risks CIOs should be paranoid about, where I stated, “As a digital transformation leader and former CIO, I carry a healthy dose of paranoia. Call it survival instincts.”

Two types of genAI opportunities in digital transformation

Tactical genAI drivers are important but not sufficient. The world is changing too fast, and genAI has enormous potential for disruption. I’ve keynoted events on AI governance and spoken to many CIOs. Unfortunately, too many are focusing on risks and incremental, non-transformative drivers.

This article focuses on several types of genAI opportunities in digital transformation. These genAI opportunities

• Focus on growth and improving customer experiences
• Balance AI opportunities with risk remediation
• Aim to transform the culture and improve human intelligence
• Transform operations top-down with genAI as a foundational capability

Thanks to ten experts who shared their recommendations.

10 missed genAI opportunities in digital transformation

1.     Drive AI innovations without understanding regulations and responsibilities

“Organizations, especially in high-risk industries like healthcare, finance, and law, may be missing the boat on AI-enabled risk- and compliance solutions that could greatly streamline the process of meeting constantly changing AI-driven regulatory requirements,” says David Talby, CEO of John Snow Labs. “Getting proactive about deploying responsible AI solutions is the best way to stay ahead of looming AI legislation and ultimately deliver safe, accurate, robust, and unbiased solutions.”

Recommendation: Review my recommendations on developing AI governance that addresses risks, regulations, and strategic opportunities.

2.     Focus too much on AI productivity without evaluating end-user experiences

“CIOs should champion a design thinking approach, bringing together well-rounded teams to map customer journeys and employee workflows,” says Ken Drazin, director of digital experience at CDW. “This collaborative process will reveal hidden opportunities to leverage technology and create seamless, impactful experiences. Think beyond technology implementation and focus on the ‘experience outcome.’ What tangible benefits will your use case deliver to customers, employees, and the bottom line? Define clear metrics and measure success from the start to ensure your initiatives drive true transformation.”

Recommendation: See a recent post on how CIOs drive amazing employee experiences by promoting hybrid work, improving developer experiences, and delivering customer service capabilities.

3.     Overdrive tactical AI improvements instead of driving transformation

Mike Connell, COO at Enthought, says, “Adopting new technologies follows a predictable course: initially, people look for ways to do what they do today faster, cheaper, and better. CIOs seeking transformational genAI use cases must look beyond initial incremental improvements and consider how genAI can fundamentally reshape their core business.”

Connell shares two examples:

• Rather than using AI to improve individual meeting tasks, CIOs could explore how AI agents might replace traditional meetings altogether.
• AI can streamline the contract negotiation process by directly producing mutually acceptable options based on formalized goals and constraints.

“By identifying and exploiting these new affordances introduced by genAI, CIOs can drive significant value creation across customer satisfaction, revenue growth, operational efficiency, and employee productivity,” adds Connell. “The key is challenging existing constraints and redesigning ecosystems to leverage genAI’s transformative potential.”

Recommendation: Intelligent document processing like contract management may be a boring genAI use case, but regulated enterprises still have paper and PDF-heavy processes that require transformation.

4.     Pursue AI innovations without  product management disciplines

“To identify highest-impact AI use cases, CIOs must be fluent in both the potential and limitations of AI, as well as the real challenges their customers and operations face,” says Ori Yudilevich, CPO of MaterialsZone. “Product-oriented organizations have distinct advantages as they naturally integrate these perspectives into their vision and strategy. With this foundation in place, AI agents become a natural extension, seamlessly embedding themselves where they can drive meaningful impact across the business.”

Recommendation: Top CIOs pursue product management-based IT organizations to avoid overpursuing stakeholder wishlists. Review my vision statement template if your organization doesn’t have a good one.

5. Band-aid AI implementations without reengineering the data foundations

 “I predict many CIOs playing an impossible game of catchup in a few years if they neglect the data architecture underneath their AI operations,” says Joe Warnimont, security and technical expert at HostingAdvice.com. “It seems all too common for CIOs to use retrofits or to force integrations to make their old data systems work with new AI services and tools. Unfortunately, that’s like trying to build a modern city on top of a medieval sewage and water supply system. Everything on top of the foundation will be terribly constrained. I’ve seen teams spend one or two years modernizing their data architectures to prepare for implementing AI services. And that’s what’s required, not shortcuts.”

Recommendation: This is an example of pursuing interior decoration without fixing the underlying architecture and structural foundations. See my recent articles on investing in data fabrics and improving data pipelines.

6. Accelerate AI without accelerating data quality initiatives

“If CIOs aren’t thinking about their data, they are missing the most important part of genAI,” says Matt Minetola, CIO of Elastic. “CIOs should invest in the quality of their data so they know that the data they deliver and expose to genAI is accurate and reliable. That starts with localization for security, privacy, and compliance, along with a RAG strategy and platform to enhance data relevance.”

Recommendation: Data debt and data management debt are two types of tech debt that can cripple your business. See my recent article on six ways to avoid and reduce data debt.

7. Allow repetitive infrastructure incidents without addressing root causes  

“CIOs in 2025 must invest in real-time visibility across their modern data centers before blind spots in complex IT infrastructure lead to costly disruptions,” says Ryan Worobel, CIO of LogicMonitor. “It’s no longer enough for data management tools to simply flag technical incidents; they must translate complex metrics into business-critical insights that demand executive action. The CIOs prioritizing this now will drive competitive advantage, while those who don’t risk falling behind in an increasingly data-driven world.”

Recommendation: Review my recommendations on devops observability and dataops observability.

8. Drive AI innovations without seeking opportunities in IT operations

“GenAI has the potential to improve the efficiency of IT operations and can be integrated into existing tools,” says Karthik Kannan, head of product management, strategy, and operations at Nile. “CIOs should evaluate their existing IT operations tools and the potential of genAI integration to help them understand the customer’s environment, design their network more accurately, and eliminate issues that may happen downstream. GenAI can also be used to automate or hasten the resolution of network issues so that MTTR is reduced, and availability is improved.”

Recommendation: Review these breakthrough AI and DevOps innovations.

9. Scale data without standard architectures and finops practices

“As companies increasingly leverage genAI, the need and use of data will scale exponentially and quickly drive storage and compute costs up,” says Minetola of Elastic. CIOs must prioritize a solid data strategy and a scalable data storage approach. GenAI has the promise and power to leverage all your data but also exposes environmental inconsistencies.”

Recommendation: Stay tuned for my upcoming InfoWorld cloud and finops opportunities article.

10. Aim for autonomous AI instead of amplifying human-at-the-helm opportunities

“CIOs should approach AI use cases by evaluating their ability to amplify human intelligence and directly impact customers, revenue, and operations,” says Ramprakash Ramamoorthy, director of AI research at ManageEngine. “Just as search engines reshaped how we access knowledge and GPS changed our sense of direction, genAI is redefining how employees generate ideas, synthesize information, and make decisions.”

Recommendation: See my recent post on seven ways genAI helps employees with work they couldn’t easily do before.

Don’t be paranoid! Let me know if you need help with genAI opportunities in digital transformation.