AI Isn’t Software. It’s a Coworker That Needs Training.
For years, rolling out new technology followed a familiar script:
Then along comes AI, especially agents, and that approach doesn’t quite apply.
Because AI doesn’t behave like traditional software. It behaves more like a new hire. A fast one. A tireless one. One that can draft, analyze, summarize, and recommend at scale. But also one that can confidently hand you something that looks right and isn’t.
So the question isn’t just how do we train people on AI?
It’s, How do we train people to work with it?
Before we throw out the old playbook, it’s worth noting: a few fundamentals still make sense.
Your sales team doesn’t care about marketing use cases. Your CS team doesn’t care about pipeline generation. Relevance is still oxygen.
“Here’s how to cut content generation time by 90%” will always land harder than “here are 12 general capabilities.”
Executive sponsorship, clear expectations, reinforcement loops; none of that goes away. If leadership expects everyone to just “be productive!”, sub-optimal adoption follows.
Office hours, quick wins, internal champions; same story, new tool. So far, nothing shocking. Now for the parts that are quite different.
Traditional tools are procedural.
Do this → then that → get result.
AI is interpretive. It requires users to constantly evaluate:
That’s not a workflow. That’s a mindset. That’s not a typical part of training.
This is the part people underestimate.
AI is only as good as the instructions it’s given. A lot of people aren’t well-versed with AI prompting, at least at first. Same thing with the early days of using Google.
Think of it like managing a very capable intern with zero context:
Training needs to include:
Otherwise, users hit friction early and don’t reach the promised productivity..
Most software behaves predictably (deterministically). AI doesn’t always.
Agents can evolve:
Agent behavior isn’t frozen in time. The expectation should be:.
“This is how it works now. It will learn and evolve every day.”
With traditional software, misuse is limited. With AI, misuse can scale…fast.
Training needs to clearly define:
This isn’t a feature conversation. It’s a boundaries conversation.
Most users fall into one of two camps:
Both are risky. The goal is a middle ground:
AI is powerful. And I’m still responsible/in charge.
That balance doesn’t happen by accident. It has to be taught, reinforced, and modeled.
This is the quiet shift that changes everything.
Software helps you do tasks.
AI helps you think through tasks.
That means training needs to cover:
In other words, you’re not just teaching usage. You’re teaching partnership.
They train AI like it’s Salesforce, a marketing platform, or a project tool.
Feature walkthroughs. Navigation demos. Maybe a few canned examples.
Then they wonder why adoption stalls.
Because none of that teaches people how to work with AI in the flow of real decisions.
If you want this to stick, flip the model. Start here:
What slows each role down today? Start there.
Give people the language to get useful outputs.
Teach them how to spot strong vs. weak responses.
Be explicit about risk, data, and boundaries.
Not sandbox examples. Actual tasks they care about.
When AI adoption lags, it’s because people don’t know how to use it well, not its lack of capabilities.
And in a world where everyone claims AI will make them faster, cheaper, and smarter, the companies that win won’t just have the best tools.
They’ll have the best-trained humans working in partnership with AI.
As this infographic illustrates, a mature advocacy program is responsible for continuously identifying advocates, maintaining accurate advocacy data, protecting customer relationships, and aligning with top company goals to accelerate growth.
The infographic contains six key components. Here's a description of each for you to translate into your own talking points.
Every advocate starts as a customer.
The journey begins when account teams, customer success managers, support teams, and services organizations create positive experiences that build trust and confidence.
As customers achieve success, some become enthusiastic supporters of the company, its products, and its people. These customers are identified as potential advocates and introduced to the advocacy team.
The advocacy team interviews these individuals, learns about their experiences, captures important details about their interests and expertise, and creates a searchable advocate profile.
The result is a discoverable advocate: someone who can be found, matched, and engaged when the business needs credible customer voices.
Without this process, valuable customer relationships remain hidden inside co-workers’ heads or team spreadsheets, unavailable to the broader organization.
Great advocates are rarely discovered by the advocacy team alone. It’s really just too much to ask of any one part of the organization. Every customer touchpoint plays a part in cultivating and retaining advocates.
Customer success managers see customer enthusiasm firsthand. Account teams hear success stories during business reviews. Support teams witness customer loyalty. Product teams interact with passionate users who influence future direction.
A successful advocacy program creates a systematic way for all customer-facing teams to identify and nominate potential advocates, as well as a means for customers to self-identify..
Think of it as building a talent pipeline.
The broader the participation across the organization, the stronger and more diverse the advocate community becomes.
This collective effort ensures the advocacy database reflects the full spectrum of customer success stories across industries, products, geographies, and use cases.
The advocacy team serves as the steward of the organization's advocacy data.
Their responsibilities fall into three primary areas.
First, they recruit continuously. Advocates change jobs, priorities shift, and customer enthusiasm naturally evolves over time. Maintaining a healthy advocacy community requires constant replenishment.
Second, they keep information current. Customer stories, product deployments, business outcomes, and willingness to participate all change. Outdated advocacy data quickly becomes unreliable.
Third, they measure and report value. Advocacy programs must demonstrate their contribution to business outcomes such as customer acquisition, retention, and expansion.
Beyond maintaining records, the advocacy team actively shapes the composition of the database to align with company growth objectives. This is essential if the program is to be seen by executives as a strategic lever vs. a low-level function an intern can run.
If the company’s strategic direction includes expanding into healthcare, launching a new product, selling through a new channel, entering Asia, or targeting a specific buyer persona, the advocacy team ensures the advocate population evolves accordingly.
In many ways, they function as portfolio managers for one of the company's most valuable assets: customer credibility.
Most organizations initially think of advocacy as a sales resource.
Sales certainly benefits from customer references, but advocacy creates value far beyond the sales organization.
The common thread is credibility.
Advocates provide something no marketing budget can purchase directly: authentic proof from real customers.
Most mature advocacy programs include additional components that extend value for both advocates and the business.
These activities are connected mechanisms that strengthen relationships, increase engagement, and create additional opportunities for customers to contribute.
Together, they help transform advocacy from a transactional activity into an ongoing customer experience.
The ultimate purpose of customer advocacy is not activity.
It is business impact.
In Summary
Advocates are valuable assets. The advocacy team's job is to make sure those assets are available when needed, protected from burnout, and aligned with the organization's most important priorities.
When done well, customer advocacy transforms customer success into measurable business value. It is an enterprise capability built on trusted relationships, reliable data, and authentic customer voices.
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