Achieving operational impact

Do we have to go all-out into a world of autonomous AI agents, and pick a new AI-first sales and marketing platform? I'm suspicious about this.

I think these tools need data, and in my experience, sadly most data for decision-making is fragmented and doesn't flow with time as a signal. Two examples:

1. CRMs and spreadsheets have become a pillar of management reporting, but they are often snapshots: other than finance, most business intelligence about projects, win rates, marketing pipeline and other fundaments are assembled over points in time by senior staff. A consistent baseline and graph of forward-looking predictions (with an explanation of what went into those predictions) is a rare and precious thing.
2. AI systems can read, understand and model how different signals hiding in your reporting layers are actually related to each other (and LLMs are good at consistency if you know how to ask). Assembling and preparing time-series data and orchestrating AI tools around it gets you to the predictive tools. I really have seen this flourish.
3. Org. charts tend to silo teams and their records, and knowledge tends to be subjective, tribal or lost in fleeting moments.

Technical support conversations might be the best place to discover upselling opportunities; closed-won sales calls might be the best place to find out about competitors; a BDR rejection might trigger just the engineering insight a developer needed to know - but these are all very loosely coupled. In most businesses, there is situational awareness in each team, but not formal and objective records. Weekly standing meetings and hierarchical reporting weakly support knowledge spreading; they give a voice to people who know something important, but this is fundamentally an unstructured environment, not data science.

The opportunity: AI can reason through troves of unstructured data and find the trends, and do so consistently, repeatedly, and with grounded goals in mind. Just having an LLM find patterns in emails and calls transcripts is a whole new class of data, and over time it's where there's rich, untapped decision-making potential.

What's better than new software and tools? If you can gather and organise signals that relate to customers anywhere in their journey with your company, to me, that's better than changing your CRM or upending your GTM strategy every quarter. I truly think recognising how to gather and store the data matters more than picking the AI tools. That comes later.

You're grounded in the real specifics of your industry and your own operating model, and have years or decades of clear thinking and experience on your side. There's no rug-pulling for new software and tools involved, just a focused effort to recognise what's there and start leaning into AI to pick through it.

That's the approach we take on every engagement, and it's why most of our systems are in daily use within weeks of the first conversation. If you'd like to talk about an in-house AI for your own team, get in touch.

Author: Michael Wells