Your Company Is Doing AI Strategy Wrong If You're Doing Any of These Four Things
- Rebecca Thachil
- 4 days ago
- 4 min read
Over the last year, I’ve watched multiple teams invest in AI in all the wrong ways. They’re excited, they’re curious, and they’re willing to experiment… but they’re placing energy in the wrong areas. As a result, they end up with no ROI, no measurable improvements, and no operational change — which is exactly what they wanted to avoid.
If your organization is doing any of the following, your AI strategy is fundamentally broken (but fixable).
1. Your CEO Asked You to "Have an AI Strategy" — and Your Response Was to Start Researching AI Tools
If the first step in your AI strategy was to Google “best AI tools for sales” or sign up for a handful of trials, that’s not a strategy. That’s panic research.
AI strategy does not begin with tools. It begins with business problems, bottlenecks, and opportunities.
When leaders jump straight into tool discovery, they end up with:
Random tools adopted for the sake of saying “we’re using AI.”
No alignment between technology and business goals.
Confusion among teams because no one knows why this tool was purchased.
A stack of unused AI subscriptions with no measurable impact.
A real AI strategy should start with one question: What outcomes are we trying to improve?
Examples include:
Speeding up opportunity creation
Increasing outbound volume
Reducing renewal prep time
Improving forecasting accuracy
Reducing manual data entry
Preventing pipeline decay
Once the outcome is identified, then — and only then — does tool selection make sense.
Skipping this foundation is how companies waste money, time, and trust.
2. Your “AI Strategy” Is Giving Your Teams Access to a Paid ChatGPT Account
I see this everywhere: a company buys ChatGPT Plus or Enterprise access for the team and announces, “We now have an AI strategy.”
Providing access to ChatGPT is not a strategy. It’s the equivalent of giving your sales team access to Salesforce and expecting revenue to magically increase without process, training, or structure.
AI tools require:
Purpose
Enablement
Guardrails
Workflows
Integrations
Measurement
Ownership
Training
Without these, ChatGPT becomes nothing more than a convenience tool that helps people write slightly faster.
What’s worse is that companies often assume adoption = success. They’ll say:
“Everyone is using ChatGPT, so our AI strategy is working.”
No. Your teams using ChatGPT casually does not mean AI is embedded into the business. It simply means your employees found a faster way to write things.
A true AI strategy defines when, how, and why AI is used — and it ensures the usage creates measurable outcomes rather than noise.
3. You Think Your Sales and CS Teams Are Strategically Using AI, But They’re Really Just Using ChatGPT to Draft Emails
This is the biggest illusion companies fall into.
Leaders proudly claim: “Our teams are using AI every day!”
When you look closer, the “usage” is nothing more than:
Drafting emails
Polishing messages
Rephrasing things
Summarizing customer complaints
Writing meeting follow-ups
This is the equivalent of giving someone a spaceship and watching them use it as a flashlight.
Email writing is not AI strategy. It’s table stakes — basic utility — and provides minimal competitive advantage.
Strategic AI usage looks different. It includes:
Territory planning with predictive scoring
Automated lead enrichment and routing
AI-driven ICP detection
Dynamic account prioritization
Renewal risk scoring
Conversation intelligence tied to actual win/loss patterns
Forecasting models based on historical behavior
AI-powered QBR prep
Automated pipeline hygiene
Continuous rep coaching
If AI isn’t helping your teams sell faster, close stronger, identify opportunities earlier, or remove manual tasks entirely — you don’t have AI strategy. You have AI convenience.
4. Your AI Strategy Has No Goals, No KPIs, and No Targets
If there is no measurable number attached to your AI work… You don’t have strategy. You have experiments.
AI strategy needs a metric. Multiple metrics, ideally.
For example:
Increase outbound productivity by 25%
Reduce SDR time spent on research by 40%
Improve SQL→Opportunity conversion by 10%
Reduce QA time for forecasts from 4 hours to 30 minutes
Increase renewal preparation speed by 50%
Reduce time to generate proposals by 80%
Improve deal cycle speed by 15%
Without this, you can’t evaluate:
If the AI tool works
If the workflow is helping
If adoption matters
If ROI is real
If the cost is justified
If this should expand or be scrapped
Every AI initiative should answer one key question: What number will this change?
If no number is attached, your AI work becomes invisible — and leaders eventually conclude that “AI didn’t work,” when the real issue is that success was never defined.
Final Thoughts: AI Strategy Isn’t About Tools — It’s About Transformation
An AI strategy isn’t something you buy. It’s something you build — intentionally, cross-functionally, and with clear business outcomes in mind.
If your company is:
Collecting tools without a plan
Handing out ChatGPT licenses and hoping for the best
Mistaking casual usage for strategic value
Operating without metrics or measurable outcomes
…your AI strategy is heading in the wrong direction.
The good news is that this is easy to fix once you shift the focus from:
❌ “Which tools should we use?” to ✅ “Which parts of our revenue engine can AI measurably improve?”
When you anchor AI to business outcomes, RevOps becomes the natural owner of AI strategy — ensuring the workflows, data, processes, and performance improvements are not only implemented but also measurable and repeatable.
If this resonates, this is exactly the kind of conversation happening inside Reklik. It’s a community for GTM and RevOps leaders who want to move past AI hype and focus on workflows, outcomes, and measurable impact. If you’re looking for practical examples and real discussions around what actually works, you’ll feel at home there.
