5 Signs Your AI Strategy Is Jiberish (and How to Fix It)
Most AI strategies read beautifully and ship nothing. The deck is polished, the vocabulary is current, and six months later there's still no software in front of a customer. Here are five tells that an AI initiative is jiberish — and the specific move that turns each one around.
1. The goal is "adopt AI," not solve a problem
"Adopt AI" is not a goal; it's a press release. Real initiatives start from a painful, specific problem — slow onboarding, manual triage, a report nobody has time to write — and treat AI as one possible tool.
I sat through a leadership offsite where the OKR was literally "become an AI-first organization." Nobody could name a workflow that would change on Monday. The budget was large. The problem list was empty.
Fix it: Write the goal as a sentence a customer or frontline operator would recognize. "Cut time-to-first-draft for customer proposals from two days to thirty minutes" is a goal. "Leverage generative AI across the value chain" is not. If you can't write the sentence, you're not ready to build yet.
Smell test: Delete the word "AI" from the goal. If nothing meaningful remains, you don't have a problem statement — you have a fashion statement.
2. There's a roadmap but no shipped surface
Endless discovery is a symptom. If every milestone is another workshop, another audit, another vendor evaluation, the work has become its own product.
A healthcare wellness org I advised had a twelve-week "AI discovery" plan with six vendor demos and zero planned production surface. By week eight they knew more about the market and still hadn't changed an employee's Tuesday.
Fix it: Commit to one shipped surface — a single feature, in production, used by real people — inside three weeks. Constraints force clarity. Discovery that can't name the first surface is procrastination with a facilitator.
Smell test: Look at the next thirty days on the roadmap. Count workshops vs. ship dates. If workshops win, the strategy is a calendar, not a build plan.
3. Success has no number
"Improve efficiency" can't be passed or failed, so it never is. Without a metric, every result is a success and nothing improves.
I've watched teams celebrate "positive sentiment" from a pilot while the underlying cycle time didn't move. Sentiment is easy to collect. Reality is harder — which is why jiberish strategies prefer it.
Fix it: Pick one number and a baseline before you build. Time-to-resolution, conversion, hours saved, percent of deals with a prep doc — any honest metric beats a vibe. Write the baseline on the first slide, not the last.
Smell test: Ask "what number, on what date, would make us kill this?" If the room can't answer, you don't have a success metric — you have a hope.
4. The plan depends on a model that doesn't exist yet
Strategies that hinge on capabilities arriving "soon" are bets, not plans. The model you can use today is the only one you can ship on.
I've reviewed decks that waved at "multimodal agents arriving next year" as the reason not to ship a boring text workflow now. Waiting for the future model is how teams stay in slideware while competitors ship ugly v1s.
Fix it: Design for current capabilities. If a future model makes it better, great — but the value has to land with what's available now. Put "depends on future model" items in a parking lot, not in the critical path.
Smell test: Cross out every bullet that requires a capability you cannot demo today. If the plan collapses, it was never a plan.
5. Nobody owns it after launch
A pilot with no owner is a demo with a countdown. The moment the consultants leave, it rots.
A B2B SaaS team shipped a promising internal copilot with "shared ownership" across product, ops, and an external vendor. Twelve weeks later, nobody knew who was allowed to change the system prompt. Usage died. The postmortem blamed "change management." The real cause was an orphan.
Fix it: Name the owner before the build, not after — one human with authority to change prompts, kill features, and answer "is this broken?" Hand off working software and the know-how to run it. Ownership includes the boring ops: eval inputs, boundary doc, and a weekly check that the thing still works.
Smell test: Ask who gets paged (metaphorically) when the AI feature is wrong on a Tuesday. If the answer is a committee, you don't have an owner.
Advisory vs. build: where the time actually goes
Anonymized strategy-deck teardown
I was asked to review a 34-slide "AI transformation roadmap" for a mid-market B2B company. Names stripped. Pattern intact.
What the deck had:
- A vision statement with "AI-powered" three times on page one
- A maturity model copied from a vendor
- A three-horizon roadmap (explore / expand / transform)
- A vendor shortlist with logos
- A RACI that listed eight teams and no single owner
- A success section titled "KPIs" that named "adoption," "innovation," and "competitive differentiation" — zero baselines
What the deck lacked:
- One sentence naming the first user-visible problem
- One production surface with a date inside 30 days
- One kill criterion
- One named human who could change the system after launch
- Any mention of what stays human (boundaries)
What I recommended instead (one page):
- Problem: proposal first drafts take two days and stall deals in late stage.
- Surface: in-product draft assistant for AEs, production in three weeks.
- Metric: median time from opportunity stage X to first customer-ready draft; baseline this week.
- Owner: [name], product + one AE champion.
- Boundary: AI drafts; AE sends; no customer data outside approved tools.
- Kill: if median time hasn't moved in 30 days post-launch, re-scope or stop.
They didn't need 34 slides. They needed a shipped surface and an honest number. The rewrite fit on a page. The original deck was jiberish with excellent formatting.
A one-page strategy rewrite template
If your current deck fails three or more of the signs above, don't schedule another workshop. Fill this instead — one page, shared with whoever controls budget:
Problem (customer/operator language):
First shipped surface (who uses it, where it lives):
Ship date (≤ 3 weeks):
Baseline metric + target:
Owner (one name):
What AI must never do:
Kill criterion (date + number):
If the page is hard to fill, the strategy isn't under-documented — it's under- decided. Filling the blanks is the work. Decorating a 40-slide roadmap is the avoidance pattern.
The throughline
Every fix above points the same direction: smaller scope, real software, honest numbers, clear ownership. That's not anti-AI — it's how AI actually earns its place. Cut the noise, build the thing, and tell the truth about the rest.
If you want a blunt read on where you stand before another roadmap cycle, take the free readiness scorecard. If the gap is install-and-ship help rather than another deck, look at services or the GTM AI Operating System.
Frequently asked
If a focused proof of concept can't show real, in-context value within two to three weeks, the scope is wrong or the problem isn't a fit. Long POCs usually hide unclear success criteria.
Usually not at first. A small team that already owns the product can ship meaningful AI features faster than a separate 'AI team' that has to learn the domain. Embed the capability, don't silo it.
Advisory gives you a plan, architecture, and best practices you can act on. A build is the shipped software itself. Most teams need a little of the first and a lot of the second.