For CTOs and Heads of AI in service-first organisations, it’s an interesting time.

The number one board priority is to determine how you’ll use AI as part of your strategic offering as well as improving everything you do. Bonus points if you create net new AI-first products & services that are only possible because of AI, and further differentiate you company from the competition and provide new levels of ROI unachievable before.

The imperative is no longer just “use AI”; it’s “embed AI as a strategic offering.”

But where do they start? AI solutions are only as good as the data they have access to.

We’re in a fortunate position to provide AI leaders with the most precious dataset they could hope to leverage; communication data in their organisation.

We’re seeing first hand what AI leaders are working on across our mid-market and enterprise clients and there are three types of high-value use cases emerging by leveraging the communication data Kaizan unlocks.

The Top 3 Ways Heads of AI Are Extracting Value from Client Communication Data

As a preface to our upcoming State Of AI In Account Management 2025, here are the top three ways we’re seeing AI leaders leverage communication data housed in Kaizan to level-up their organisation.

1. Knowledge-graphs: internal know-how from client, supplier and internal communication.

You may already have a shared AI workspace including your company documents that employees can query. But it’s static and requires manual updating. Imagine how rich your team’s collective intelligence would become if you captured key intelligence from from calls, emails, chat as well as documents!

Building searchable knowledge graphs that map: services, deliverables, client preferences, onboarding templates, all-hands conversations and strategic account histories.

Why? Because the average knowledge worker spends ~10 hours/week searching across their tools and systems for answers.

By turning unstructured comms into structured, queryable knowledge, these companies are reclaiming lost time and preserve institutional memory.

2. Custom workflows: downstream from communications.

Each company has existing workflows they’d like to automate. Previously, humans took action to complete these tasks after receiving the email or after being on the call.

With structured comms data, enterprises are deploying intelligent agents that trigger downstream workflows for common use cases: generating ad-concepts, scripting content, qualifying new-business calls against custom rules, routing action-items, updating Project Management tools etc.

This isn’t peripheral, it’s becoming mainstream. Research shows up to 60-70% of work activities across organisations could be automated!

By using comms data to trigger workflows, service-first organisations reduce latency, errors and misalignment and we’re seeing very interesting use cases emerge.

3. BI/ops dashboards using real-time communication signals.

Sentiment trends, product and service feedback, response-times, talk-time distributions, topic analysis. All can be drawn from real client interactions and are crucial data sources for BI teams.

Analysing interaction data gives real-time insight into what is actually happening across an organisation, with clients, and with the market.

When comms become a data asset, you move from “lagging” metrics (CSAT, NPS) to leading indicators of risk, growth and efficiency.

Why This Matters for AI/CTO Leaders

>> Knowledge infrastructure underpins scalable service delivery and reduces risk of knowledge attrition when teams or clients change.

>> Workflow automation tied to client communications unlocks real productivity gains and positions operations for scale.

>> Comms-driven BI gives you an early-warning system and strategic dashboard for client health, company efficiency and expansion potential.

As one McKinsey report put it: while nearly all companies invest in AI, only ~1% believe they are truly mature in its deployment.

At Kaizan, we’re fortunate to see how the 1%, the companies at the frontier, are leveraging their richest most precious dataset to reimagine how they operate.