What You’ll Find This Week

AI is upending…just about everything. Including innovation mandates. In 2026, we expect AI — truly applied, functional, useful AI — to be the focus for most orgs. And while AI sounds “cutting edge” and therefore aligned to innovation, the reality is that we’re still too early in the hype cycle for innovation and AI to be perfectly aligned.

Over this week and next, we’ll break down the Innovation Mandate in 2026 to help you align the practicalities of advancing AI within your org to the realities of focusing on innovation when the two aren’t entirely aligned.

Here’s what you’ll find:

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This Week’s Article

The mandate of 2026 is simple: do more with less, and do it with AI.

The proof is everywhere. “AI” is now a default topic at the top of the org. It showed up on a record 306 S&P 500 earnings calls last quarter. And IT budgets are still growing. Gartner expects worldwide IT spending to reach $6.08 trillion in 2026 (up from $5.54 trillion in 2025) with growth driven heavily by AI infrastructure and GenAI features that increase software costs.

As a result, headcount stays flat but targets don’t. Teams are told to get with the program: ship more with the same, or fewer, people. Use AI more. CFOs are also calling out tariff uncertainty and price pressure heading into 2026.

Now translate that into operating reality.

“Use AI more” doesn’t show up as extra people, extra time, or extra budget. It shows up as new obligations. Data cleanup. Access controls. Security reviews. Model governance. Platform bills. Vendor renewals.

At the same time, the tone at the top is shifting from excitement to proof. Leaders are hearing the same question from boards and investors: when does AI spend turn into real returns?

Inside a big org, “innovation” usually starts as a small new thing: a workflow change, an automation, a new tool. Try to ship one and you’ll get the three-question exam: What metric moves? What can go wrong? How do we roll it back? If you can’t answer fast, it doesn’t ship.

That exam is the system in action. It turns “new” into a tax: extra reviews, extra stakeholders, extra justification. Over time you stop building and start negotiating.

That’s how smart operators get stuck. Not from lack of ideas. From the approval mechanics that treat anything new like risk to be contained.

Don’t sell innovation. Sell the outcome the org already rewards, then ship the new thing underneath it.

Innovation teams are getting squeezed from both sides.

From the top: “Use AI more.” Which really means “make AI safe, governed, and defensible.” So your roadmap fills up with data cleanup, access controls, model governance, security review, procurement, and rollout controls.

From the side: “Do more with less.” Which means the org has less patience for anything that looks like learning, and less bandwidth to adopt changes that disrupt the week.

So innovation stops being “discover new growth.” It becomes “deliver productivity without breaking anything.”

You’re staffed to explore uncertainty. The mandate funds certainty. And the moment you try to ship something meaningfully new, the approval system treats it like risk to be contained.

That three-question exam is the approval system. Miss the metric, the risk story, or the rollback, and you’re back in the queue.

When the mandate is AI plus efficiency, “new” usually touches data, security, vendors, and reputation. That pulls you into a predictable stack of gates.

It’s predictable. It’s also why change stalls.

It approves work that looks like:

Don’t pitch the innovation. Pick the outcome the org already rewards. That outcome is your cover. Pitch the outcome that clears the gates. Ship the innovation underneath it.

In 2026, you won’t get funded for novelty. You’ll get funded for outcomes that reduce load.

A demand substitute is one of those outcomes. It’s what your org already buys without debate because it reads like productivity, risk control, or core stability.

Attach your change to that outcome. Keep the first version small. Produce proof fast.

That’s how you innovate without an innovation mandate.

These are the outcomes that clear gates in 2026. Pick one primary substitute for your next move.

What it is: preventing future spend from incidents, rework, and tool sprawl.

Why leaders say yes: it reads like stewardship, not a gamble.

Default metric: dollars avoided, hours of rework avoided, tool count reduced.

Proof artifact: a before/after cost line or deprecation plan with an owner and date.

What it unlocks underneath: platform consolidation, workflow redesign, automation, retiring legacy.

What it is: shrinking the chance of a public failure. This includes model risk and data exposure risk.

Why leaders say yes: it protects delivery and reputation.

Default metric: number of high-severity risks closed, exceptions reduced, incident rate or severity down.

Proof artifact: a one-page risk register with “closed” items, plus a rollback plan.

What it unlocks underneath: prototypes, limited pilots, customer tests, changes that would normally be blocked as “too risky.”

What it is: reclaiming hours inside a team by removing manual work, rework, and meetings.

Why leaders say yes: it increases output without asking for headcount.

Default metric: hours reclaimed per week, manual steps removed, meeting time reduced.

Proof artifact: a before/after workflow map and a calendar delta.

What it unlocks underneath: AI automation that removes a recurring step, not a demo feature.

What it is: cutting end-to-end lead time across handoffs and approvals.

Why leaders say yes: faster delivery shows up immediately on the dashboard.

Default metric: days from request to ship, queue time, handoffs per request.

Proof artifact: a simple timeline showing where days get spent, before and after.

What it unlocks underneath: decision-right changes, gate reduction, standard paths, tooling that speeds delivery.

What it is: eliminating a recurring complaint, escalation, or churn driver.

Why leaders say yes: it protects revenue and reduces noise.

Default metric: escalations per week, time-to-resolution, churn driver frequency.

Proof artifact: a before/after on one pain driver, with fewer escalations in a defined segment.

What it unlocks underneath: new workflows, better self-serve, service design changes, product fixes that stick.

What it is: making compliance boring and repeatable. AI governance is now audit work.

Why leaders say yes: it reduces surprise and personal exposure.

Default metric: control coverage, exception rate, time to produce evidence.

Proof artifact: documented controls plus monitoring in place for one high-risk area.

What it unlocks underneath: data flows, access patterns, logging, and guardrails that let you ship faster later.

This is the playbook. Don’t pick the most exciting substitute. Pick the one you can prove fastest. The 2026 mandate sounds like momentum. For innovation teams, it’s a constraint.

In Part 1, we did three things:

Your only job before next week: pick one demand substitute you can prove in 2 to 4 weeks.

Next week, Part 2 drops. We’ll turn your pick into an execution strategy: map the buyer, use the Demand Substitute Menu, score it, run a 30-day sprint, and pitch it in a way that gets a yes.