Hi everyone – I’ve started a new newsletter to go along with my new venture, Automated Consulting Group. I’ve added you to the list because we’re connected in one way or another – working together, LinkedIn, etc.
The unsubscribe URL is at the bottom of this email if you don’t want to hear from me going forward.
Thanks for reading,
~Robbie
Robbie Allen
Founder & Managing Director
Automated Consulting Group
Most leaders I talk to think they are behind on AI.
Most of are actually a little ahead of the curve.
The tech is moving faster than organizations can absorb it, which is normal for a transformative tech trend. AI is just moving much faster than dot-com, social, mobile, etc. ever did.
If you have not started integrating AI into your work by 2026, you might start to feel a little late. Until then, pick a lane and begin.
Signal
Consumer tools set expectations your enterprise stack cannot match yet. People try things at home, then hit policy or access walls at work. That gap slows learning and creates shadow usage. Close the gap with clear access, simple guidelines, and a path to try things in the open.
Move
Commit to top down and bottoms up at the same time. Don’t issue a single vendor edict, but do set guardrails by green-lighting a small set of tools and use cases. (Though you should also make it easy to request an exception to try new tools and ideas.)
Ask teams to bring back two things they tried each week and one thing that stuck.
Your goal should be to encourage experimentation.
Proof
Habits are the unlock.
I coach execs to treat an AI model like a PhD-level assistant that never sleeps. Use it to ideate, draft, and unstick hard problems.
The hard part is not picking a tool. The hard part is remembering to open it on the tough email, the sticky negotiation, or the blank page.
What to build now
Pick repeating work that touches revenue, cost, or risk. Favor lightweight copilots that remove friction from existing workflows. Avoid big platform bets that require a reorg to matter.
Be skeptical of agent claims that promise end-to-end automation — we’re just not there yet. Instead, use models to get better answers faster, then connect those answers to the systems that move numbers.
Good pilot candidates
Support replies for the top ten intents. Measure handle time and error rate.
Sales call prep and follow-ups. Measure prep time and meeting outcomes.
Policy or contract summaries. Measure reviewer time and redline cycles.
Internal knowledge search across docs and tickets. Measure search time saved.
How to know it is working
You will see behavior change first. Executives open a model during reviews. Managers ask for prompts like they ask for templates. Front line teams clear the blank page faster and shave minutes off common work.
Track adoption in a few target workflows. Keep what moves a number you care about. Roll back what slows people down.
Pitfalls to avoid
One big announcement with no follow-through.
Tool mandates that shut down exploration.
Demo theater with no change in daily work.
Waiting for a perfect ROI model before you start.
Where this is heading
Most companies can move from AI curious to AI enabled, then AI first. The ones that win pair a clear executive stance with room to experiment. They ship small, steady improvements. They measure results. They keep going.
Your 30-minute weekly workout
Here is a weekly workout that you can share with your team today:
Ten minutes on education. Read one credible update. Write one sentence on why it matters to your business.
Ten minutes on a real workflow. Pick a recurring task. Write down the time it takes today. Think about how you can use AI to create small improvement in time or error rate. Test, learn, and iterate.
Ten minutes on adoption. Ask a colleague what slowed them down. Fix one policy or access snag.
Do this every week across your organization and it will become the largest upskilling wave your company has seen.