In recent blog posts, I’ve defined what we mean by “AI-led” and how we’re building it into the Entelligence Platform. Today, I want to dig into our why.  

The raison d'être of the Entelligence Platform is to refocus professional services efforts on the outcomes they deliver. The legacy model for delivering services has been so bogged down from decades of overhead and processes that it has lost its way. Big consulting companies are hyper-focused on tactics and billable hours, and their clients struggle to see the value. 

Independent software vendors (ISVs), IT leaders, the channel, and consultants alike all keep running into the same barriers: 

• Services can’t keep up with the pace of software. 

• Every consulting engagement feels custom, even when it shouldn’t. 

• Hiring or scaling delivery teams is slow and expensive. 

• Institutional knowledge lives in people’s heads, not in a system. 

Our goal is to give every stakeholder in the services ecosystem a way to move faster, reuse what already works, and still get the human guidance that’s essential to change management.  

Let’s look at how that shows up in real use cases, and what kinds of results teams can expect. 

Built to Flex Across Very Different Services Needs 

One of the most important design principles of the Entelligence Platform is flexibility. We know not everyone is trying to do the same thing. A SaaS vendor trying to raise professional services attach rates or accelerate product adoption is very different from an enterprise IT team trying to roll out a new security platform across multiple business units. But the underlying motions are similar enough that a flexible, AI-led foundation can support all of them. 

Here are four common use case patterns we’re addressing with the Entelligence Platform: 

1. ISVs’ product adoption hinges on the ability to deliver services at scale. 

The challenge: A fast-growing ISV has more customers buying their latest product or version than their internal services team can implement. Meanwhile, their Sales team depends on services to get customers up and running with new solutions quickly, so they can prove value and expand utilization.  
 
ISVs don’t want to spin up a huge delivery org, yet their channel isn’t always trained on the nuances and deployment methods that are specific to each product or even each major version release. 

How AI-led helps: Journey Maps turn vendor deployment playbooks into prescriptive, repeatable paths that both consultants and end customers can follow, so every customer follows established best practices and deploys in the “official” way, not an improvised one. 

Talent Matching finds consultants who’ve actually worked with that stack and that deployment pattern before. 

Result: The ISV can say “yes” to more services without adding headcount. They protect their net retention rate (NRR) because customers realize value faster, opening the door to faster and bigger upsell or expansion opportunities. 

This is the “serve more customers without sacrificing quality” promise I talked about in the first blog in this series — and an AI-led platform is what makes that promise operational. 

2. IT leaders want faster adoption (and fewer surprises) of new tech. 

The challenge: An IT leader is rolling out a new observability or security solution within a complex, hybrid environment. Historically, engagements like this drift: scope expands, integrations take longer, and internal stakeholders lose patience (and interest). 

How AI-led helps: Journey Maps lock in a realistic, vendor-aligned implementation path on day one.  

As the project progresses, the Platform can update the plan to reflect milestones and blockers, so change management isn’t locked in a spreadsheet.  

Result: IT leaders finally get what they’ve wanted for years: predictable, transparent delivery that matches business timelines. 

This is what we mean when we say AI-led doesn’t replace humans. It just makes the work more predictable and reliable. 

3. Channel partners aim to serve more, with less overhead. 

The challenge: Channel partners want to support more of their customers’ and partners’ post-sale needs, but can’t carry deep expertise for every product they sell across numerous ISVs. 

How AI-led helps: An AI-led Platform gives them access to deployment journeys, resources for implementations, and right-fit talent on demand. Instead of turning customers away or doing “best effort” projects, partners can wrap services around more products — even newer AI capabilities — and still meet or exceed delivery standards. 

Result: More wallet share with less delivery risk. 

This is how the Entelligence Platform becomes a true services capacity extender for the channel. 

4. Consultants want to maximize earning potential, while doing work they love.  

The challenge: Great consultants don’t want to spend their time rewriting SOWs, re-creating the same runbooks, or sitting in procurement purgatory. They want to solve problems and allocate their time wisely. 

How AI-led helps: The Platform handles the repeatable parts — scoping, matching, milestone tracking.  

Onboarding processes and paperwork are streamlined and condensed down to minutes instead of weeks.  

During engagements, consultants are served the right content, best practices, and delivery guidance at the right moment. 

Result: Consultants can support more engagements at once, without sacrificing quality, and with higher job satisfaction. 

These critical humans are elevated by AI – not replaced. 

Outcomes, KPIs, & Success Metrics 

Measuring the impact of professional services has traditionally been an inconsistent practice. Many organizations report on hours spent, tasks completed, or the number of consultants assigned to a project — none of which reliably reflect whether the engagement produced meaningful business value. 

An AI-led, expert-delivered model requires a different approach: one centered on outcomes, not activity.

Here are some core KPIs that best capture whether a deployment is successful:

• Time-to-first-value (TTV)  

• Milestone completion rate
  

• Engagement predictability (% variance vs. scope) 
  

• End-user adoption 

• Customer satisfaction (CSAT) or net promoter score (NPS) 

• Performance improvements (latency, error rate, cost) 

Together, metrics like these help ISVs, IT leaders, channel partners, and consultants measure progress with clarity and consistency.  

Why These KPIs Matter 

Here’s the core truth: we didn’t build an AI-led services platform to showcase AI.  We built it to improve outcomes. When you pair AI with experienced delivery experts, three things become possible: 

• Precision. AI can apply the right playbook for the right product in the right environment — every time. 

• Efficiency. AI can remove the swivel-chair work between scoping, staffing, and executing. 

• Scale. AI can capture what worked in one engagement and make it available to the next 100. 

Human experts, on the other hand, bring the things AI can’t: 

• Context about stakeholders, politics, and adoption. 

• Real-world judgment about when to bend a process. 

• The ability to drive the culture change that’s baked into every IT project. 

When you combine the benefits of an AI-led approach with human expert delivery, you’ll get what early users are already seeing with the Entelligence Platform:  

Deployments that are completed 2x faster than legacy consulting models, and at roughly half the cost, because we’re not over-staffing or re-inventing the project plan every time.  

And projects are delivered with consistently high quality because the same intelligence is applied across engagements. 

What We’re Not Saying 

We’re not claiming “the AI will log in and configure everything for you.” That’s the agentic future, and we may get there in pieces. Today, what we’re doing is more pragmatic — and, frankly, more valuable in the current market: 

• We’re using AI to better scope, position, sell, and deliver services. 

• We’re using AI to make the right work happen sooner. 

• We’re using AI to create a cleaner handoff between ISVs, channels, consultants, and customers. 

That’s the innovation our customers are ready for right now. And as more engagements run through the Entelligence Platform, the system will keep learning: 

• Which delivery models work best for which products? 

• How long do things actually take versus what was scoped? 

• Which consultant profiles deliver the highest CSAT for specific use cases? 

• Which follow-on services are customers most likely to need?

That’s when AI-led services become a true flywheel, where every project makes the next one faster, cheaper, and better.  

Ready to See It? 

If you’ve been nodding along because your teams are stuck in the “services can’t keep up with software” loop, you’re not alone. Whether you’re an IT leader aiming for predictable rollouts, an ISV trying to scale professional services without adding headcount, a channel partner looking to expand post-sale capabilities, or a consultant who simply wants to do more of the work you love, an AI-led model gives you a clearer, faster, more repeatable path to outcomes.  

→ Learn more about AI-led, expert-delivered services and get started with the Entelligence Platform.