It’s 2026. Your board is breathing down your neck about margins. Your CFO is eyeing every line of the technology budget with a microscope. Meanwhile, generative and agentic AI are flashing neon signs everywhere—promising transformational gains, but sometimes delivering little more than noise. CIOs and CTOs today face this dynamic: how to do more with less and invest smartly in innovation.
In dozens of conversations with enterprise IT leaders across industries, one theme emerged consistently: cost savings remains the number-one priority. Macroeconomic uncertainty, margin compression, and shareholder expectations have turned IT investment into a sport of selective bets rather than full-scale leaps. Yet at the same time, leaders are under pressure to modernize operations, improve experiences (both customer and employee), secure their systems, and prepare for the coming wave of automation.
The answer is not “either/or.” It’s “both/and.” This post is a blueprint for IT executives who want to avoid being dazzled by hype and instead architect a strategy that updates the fundamentals and creates innovation momentum. We'll walk through four key themes where I believe business-technology leaders should focus in 2026:
AI is everywhere now. According to McKinsey & Company’s 2025 “State of AI” survey, more than three-quarters of organizations say they use AI in at least one business function. McKinsey & Company+1 Yet—and this is critical—over 80% of those organizations say they aren’t seeing material enterprise-level EBIT impact from AI today. McKinsey & Company+1
That disconnect is exactly why smart IT leaders need to apply discipline to their innovation agenda. I call this Sequential Diversified Innovation (SDI), and it has four steps:
Pick a use case where you can measure ROI within weeks or months—not years. Don’t chase the “moonshot” on day one. Maybe it’s automating post-call wrap-ups for your contact center, or deploying AI-driven spend analytics in procurement.
Launch, measure, learn. Get a win under your belt. The value of quick execution isn’t just the modest cost savings—it’s credibility. Once the business sees real results, the next phase becomes much easier.
After your first win, roll out the next pilot—preferably in a different functional area (finance, HR, ops, supply chain). Diversify the investment so your AI portfolio isn’t a one-trick pony.
This means don’t bet everything on one use case or one vendor. Portfolio diversification is as important in AI as it is in finance.
Why this matters: Too many organizations overspend on AI in one silo—say a flashy chatbot—but ignore broader strategic areas. SDI shifts the mindset to sustainable value across functions. It’s not sexy, but it works.
Historically, customer-facing and employee interactions have cycled through three core channels: voice, video and chat. In 2026, we need to recognize a fourth channel: AI.
Think of it like this: if voice, video and chat were the band, then AI is the drummer changing the rhythm. It sits beside your employees, not in front of them:
Start with some data: today roughly 20% of interactions are person-to-person (P2P), about 60% are person-to-machine (P2M), and 20% are machine-to-machine (M2M). By 2030, M2M interactions may climb above 22% as autonomous agents start doing the buying, planning, and servicing.
In this context, AI is no longer a feature—it’s a full-blown interaction channel. If your voice/video/chat stack were the band, AI is adding a whole new section of instruments.
What this means for CIOs/CTOs:
2026 isn’t just about customer experience (CX). It’s about Total Experience (TX)—the combined sum of CX and employee experience (EX). Why? Because every internal inefficiency, every clunky tool used by an employee, bleeds into your CX. Employees suffer, customers eventually notice.
My formula:
TX = Sum of CX UX scores + Sum of EX UX scores
And here’s the kicker: according to Forrester Research, firms who lead in TX enjoy 1.6× higher customer satisfaction and 1.9× higher employee engagement than their peers.
To win in TX:
Here’s where strategy meets risk. We often talk about AI in terms of productivity. But we must also confront the darker side: deep fakes. These are AI-generated audio, video, or images designed to mimic real people—and they’re becoming dangerously good.
Deep fakes aren't just fun viral clips anymore. They’re enterprise threats: executive impersonation calls, synthetic voices authorizing transactions, manipulated video messages sent to customers or partners. The target? Trust.
Here’s your playbook for 2026, distilled:
Here’s a fictionalized but representative scenario to illustrate the strategy:
A mid-tier financial services organization had already deployed chatbots in their customer service area—but hadn’t seen meaningful gains. The CIO pivoted: she selected a wrap-up automation use case in the contact center (small, focused). They measured time-spent per call, redeployed that freed time to agents, and rolled it out to operations. Next, they plugged in an AI-driven ‘recommendation engine’ into the voice channel (AI as the fourth channel). At the same time, the infrastructure team redesigned agent desktops to remove redundant tools (TX). Finally, the security team embedded deep-fake detection into executive comms and voice authorization flows (authenticity). The result? ~12 % reduction in cost per interaction, improved agent satisfaction, and zero major impersonation incidents all year.
That’s the SDI + fourth-channel + TX + authenticity stack in action.
2026 isn’t the year to throw full weight into a flashy AI project that lacks business alignment or governance. It’s the year to build an intelligent, resilient, trustworthy foundation—one where innovation happens within the architecture of discipline and value.
If you can win small, connect AI to your core channels, orchestrate all experience touchpoints, and protect authenticity at scale—you’re not simply keeping up. You’re leading.
Let’s make next year the year where AI isn’t just hype. It becomes business muscle.