What a glorious time it is to be a technology and transformation leader now during the genAI era!

I liken it to the late 1990s, when it was clear the internet would reshape businesses, driven by the fastest and boldest leaders and startups. It has parallels to the mid-2000s mobile, cloud, and social era, when asset-light businesses connected buyers and sellers through easy-to-find-and-decide user experiences and disrupted longstanding industries.

Now it’s the genAI era, with LLMs, AI agents, and fully autonomous agentic AI, creating a deep chasm between companies with AI fluency and those buried in digitized workflows that are not truly digital workspaces.

AI is only reshaping businesses

Boards and business leaders want AI to deliver productivity benefits and efficiencies. There are many enterprise-ready AI agents to leverage, along with emerging AI capabilities from growth startups. While some businesses struggle to bring AI agents to production, others are seeing ROI from the productivity improvements.

But few businesses have deployed a leapfrogging genAI capability to their customers.

We haven’t seen large e-commerce sites replace browsing experiences with AI shopping assistants. Online travel sites haven’t replaced search with AI travel agents that offer integrated experiences and handle transactions based on my itinerary and preferences, even though I can use an LLM today on one screen to develop my travel plan while, on the other screen, I make purchases. AI agents are transforming aspects of B2B sales and customer support functions, but agentic AI-driven supply chains and ecosystems are works in progress.

AI hasn’t reached customer experiences for the most part due to cost, complexity, and risk. Is the data ready? Not really. Are customers primed for a major change? Nope, they’re still recovering from UX changes driven by the pandemic era. Is it easy for IT to develop customer-facing LLM and AI agents? Only for teams with deep dev and AI expertise.

IT is only beginning to adjust to AI tools

Now let’s look inward. What do you see when reviewing the IT departments that have embraced AI?

Some teams are experimenting with vibe coding, but are we deploying these apps to production without validating the code? Not yet. We have some AI analytics to perform analysis without SQL, data science notebooks, or manual data visualizations, but we don’t have the capabilities predicted by The Matrix. Self-healing data pipelines and fully resilient infrastructure? Nope. Dark SOCs and NOCs without people responding to incidents or laboring over root causes? Not even close.

All this promises AI inside IT, but the reality is that much of the AI vision remains science fiction. Many IT departments, like business operations, are using AI to achieve the same objectives, only more efficiently and, arguably, with less skill than we’ve done in the past.

Why organizations aren’t transforming with AI yet

I’m not trying to be a downer here, just pragmatic. If you roll back to the web 1.0 and 2.0 eras, it took several years of evolution in IT practices and business mindsets before all the ingredients – leadership, people, process, culture, technology, vision, investment, and change readiness were in place to deliver transformational results.

For example, in Web 1.0, organizations needed to adopt agile practices to deliver applications. IT needed DevOps automations and culture change to get exponential value from the cloud. Organizations needed design thinking to figure out how to deliver mobile user experiences that weren’t just shrunken versions of their web equivalents.

Most organizations haven’t discovered the equivalent transformations for the genAI era. Without them, CIOs, CDOs, and CMOs will only be reshaping business, not transforming it.

An AI action plan for Digital Trailblazers

Here’s part of the problem. Inside IT, CIOs have new AI tools, but people’s roles and responsibilities haven’t changed. Many are still leading agile with rigid frameworks that prioritize scaling, but aren’t very good at driving creativity, collaboration, and self-organizing standards. DevOps in many businesses is only really for apps and APIs, and not really for databases, data science, or in dataops. We still have teammates who equate the definition of ‘done’ with deployment, with minimal testing, so it’s okay when we break things, and who treat change management as someone else’s responsibility.

And now there’s top-down pressure on CIOs to deliver ROI from AI investments. Many IT departments are laying off people or freezing hiring, expecting employees to do more with less to close operational gaps. During last week’s episode of Coffee With Digital Trailblazers, I featured several alarming statistics on level-1 hiring, which will impact IT over the next several years.

These forces – disruptive agentic AI capabilities, skyrocketed executive expectations on delivering returns, layoffs in IT, and new technologies for delivering AI innovations will force CIOs to transform their digital operating models. IT can’t deliver transformation with AI if its ways of working, including product management, agile, devops, and data practices, are optimized for the pre-AI era.

I share some more specifics in this month’s Driving Digital Standup video embedded below. Book a meeting with me if you’d like to discuss your department’s transformation to an AI-evolved digital operating model.