Navigating the Crossroads of AI and Human Readiness in IT

While not all AI is ready to deliver value, humans are even less ready to capture value. Despite 87% of employees expressing interest in AI tools, only 32% trust leadership to drive transformation. The imbalance between AI’s technical progress and workforce preparedness creates a fog on the path to value. 

CIOs must assess each AI use case for both technology and human readiness, treating them as steps on a “golden path” to success. Readiness is the key that unlocks that next level. Without this balance, organizations risk missing out on AI’s true potential.

Technical capabilities like search and content generation are ready, but AI accuracy and autonomous agents remain points of concern. GenAI’s error rates can reach 25% depending on the use case, yet Gartner finds that 84% of CIOs and IT leaders don’t have a formal process to track AI accuracy.

Build an “accuracy survival kit”— including metrics, two-factor error checking and realistic standards — to ensure AI outputs meet business needs. Decision-making agents, not just conversational agents, are essential for unlocking advanced value in areas like B2B negotiation and expert tasks.

AI implementation comes with hidden costs and ongoing training demands. For every AI tool purchased, ten ancillary costs may arise, from data management to model oversight. Vendor selection is now akin to choosing a “digital nation state,” with major hyperscalers and innovative startups offering diverse strengths. CIOs must consider not just technology, but also AI sovereignty and long-term vendor relationships to avoid model lock-in and ensure strategic flexibility.

Human readiness isn’t just about avoiding job losses — it’s about cultivating new skills and managing change. Look for a rise of “Swiss Army Knife” workers who see a problem and have enough curiosity and skill to leverage an AI tool to figure out how to solve it. These workers know how to use AI and can apply AI in any given task. To develop your team into these innovative workers, you need a modern AI literacy program to cultivate new skills like context engineering.

Change management for managers is crucial, as organizations remodel their IT departments for an AI-augmented future. By 2030, 75% of IT work will be done by humans augmented with AI and 25% of the work will be done by AI alone, demanding a proactive approach to identifying new value-creating IT work like expanding into new markets, creating additional products and services, or adding features that boost margins. Elevate your perspective to find, capture and sustain value.