Don't Fall For The Hype & Overhype
Leaders Letter 210 - Where Are We Really As Businesses With AI & 10 Actions To Take
Dear leaders, leaders know all about the challenges being faced inside businesses, not just from the revenue squeeze, the pressures to hit targets in a bifurcated market, the battle for headcount and now the pressures from new tech.
Unfortunately, the world is going through a lot, and it seems AI has got in the middle of it, and it’s impacting many people’s day-to-day.
Today’s newsletter is here to make AI actionable for you and your business.
I know most people are bored hearing about AI and the pressures associated with AI, not just which tools to use and why, but the headcount pressures (fire, not hire), the re-investment challenges and how to ensure we do this right.
Help Is Here
I wanted to tackle this head-on, and remove the AI hype (well, overhype in most cases) and help leaders to tackle what’s really happening and how to be successful.
AI Hype Vs. Reality Presentation
I put together a slide deck and a walk-through video of what is really happening on the ground, what it means and how to get ahead even if you are just starting.
The Google Slides Deck
https://docs.google.com/presentation/d/1zR3qKaYgC27leESC5UWmJdp7dAJidPgT2igfb1yy5wU/edit?usp=sharing
Here is the rundown and the most important actions to take:
AI Hype vs. Reality & Current State
Now Phase
Operational and Transformational Shift: AI is not just a technical change but is equally about change management and operational excellence - this is where most have got it wrong so far
The 3T’s Framework: Successful AI adoption is guided by: Time (saving energy), Trust (data privacy), and Truth (validating output).
The 2V’s: The output must be Validated (data, info, source) and Verified (you are happy to put your name and brand to it).
So Far - Low ROI: A survey of 5,000 knowledge workers found that 59% of AI use cases are basic task assistance, with only 2% considered advanced automation and only 15% likely to generate ROI for the business.
Focus on Problems, Not Tools: The key struggle is that many companies focus on “What tool should we use?” instead of identifying core business problems that AI can solve, such as scaling analysis or answering customer issues.
Next Phase
Adoption Phases: Most companies are stuck in Phase 1 (Ask & Answer), while the real value lies in Phase 3 (Agentic), where AI can autonomously research, negotiate, and complete transactions.
The progression is Ask & Answer → Assistant → Agentic and many are stuck in the old way of thinking, which is Phase 2 - Assistant
AEO is a New Marketing Channel: Answer Engine Optimisation (AEO) is critical, as businesses must adapt their marketing to how LLMs answer long-tail queries and recommend specific products with purchase links, like the example shown in ChatGPT.
The Next Phase: Agentic Future
Shifting User Journeys: The customer journey is evolving from the traditional path to Assistant-Mediated (AI-recommended purchase) and finally Fully Agentic (AI researches, negotiates, and completes the checkout).
Agentic Commerce ROI: Examples from Walmart and Amazon show that AI-assisted shopping sessions are driving significantly higher purchase values and conversion rates (e.g., Amazon’s Rufus assistant sessions converted at 3.5x the non-Rufus rate).
The Critical Action Items
My presentation outlines several actions for immediate implementation:
Create a detailed problems list (not a tools list) for AI to address - the only way to win AI is to address problems and build from there.
Run an AI Workshop to align departments on usage - I highly recommend external facilitators (yes, like me) vs an internal facilitator that will struggle to hold the room and follow up work required (away from a senior title)l
Budget for experimentation, as there is “no one-size-fits-all tool.” - there will be requirements from EA’ to Finance to Growth to Product for dedicated tools
Create the Company Context Doc immediately. This is a non-negotiable, living document detailing ICPs, style guides, and market positioning that every LLM will reference to prevent endless re-prompting cycles. This will help any of the major LLMs from Copilot, Claude, ChatGPT and Google Gemini (my favourite is still Gemini)
Host an AI Hackathon to solve “mid-effort, mid-reward” problems - hosting hackathons, you really see the change in front of you with the right cross-functional setup.
Appoint AI Captains and Champions to drive monthly adoption, roadmapping, and training.
Rethink Distribution: Move away from “over-polished” content and trust internal experts (developers, PMs, ops leaders) to provide authentic, screen-recorded walkthroughs of how AI is solving problems. Quality over quantity is critically important
Map Out Buyer Journeys: Add how the Assistant and Agentic phases will impact and optimise your buyer journeys. I have two exercises included for you to run through and complete
Map out reskilling and upskilling: This isn’t something I explicitly call out, however, understanding how you and your team need reskilling and upskilling with and against AI is something so many are not doing and it will protect headcount fights
Map Out AI Roles: Understand how AI will make team skills more blended and impact roles (e.g., the addition of a new AEO role and where AI will impact, say your Product and Marketing departments - this exercise is going to be essential)
I know this can feel a lot but I trust this helps you and your business. Hit reply if you would like to discuss any of this.
I am offering in-person and remote AI training so do get in touch or book a slot in with me to discuss.
Thanks for reading today and have a great week!
Danny Denhard