Vasyl Grygoriev,
Lizard Soft CEO

In the previous part, we focused on People. Precisely, the reasons why Employees having access to AI tools often ignore them.

We found out that open sabotage is more of an exception than a rule. The main problem lies elsewhere: in the lack of skills, fear of making mistakes, misunderstanding of personal benefit, or lack of time for experiments.

Today, I offer not just a set of tips, but a people-centric framework for implementation. This is systematic work that turns an indifferent or frightened Employee into a real Power User.

But here's an important caveat: you should move on to the stage of working with people only when the homework has been completed. If you still do not have clearly defined business needs, the Implementation Team has not been formed, and there is no driven Sponsor at the C-level, no amount of training will save the situation.

We will talk about this fundamental stage (the Business category from our classification) in the next publication. Today, about how to act when the strategy is already there, and it’s time to scale it into a live organization.

Who do we want to get at the output?

Before building a route, it’s worth clearly imagining the destination. Our final «product» is not just an Employee familiar with the order to use AI. We need a Power User. A Person who:

• Perceives AI not as a threat, but as a simple tool for achieving goals.
• Understands the technical capabilities and, more importantly, the limitations of the technology.
• Can apply AI to specific tasks in their workplace.
• Sees support from Management both in words and in actions.
• Has a network of Colleagues to whom they can turn for advice (Champions).
• Knows where to turn for technical assistance if «something goes wrong».
• Feels that they have every right to experiment and time to optimize their own processes.

It looks like an ideal portrait. But how to get to it in practice?

Roadmap: from strategy to habit

1. Find your Quick Win (and don’t be tempted by scaling).

The most common mistake is to try to immediately implement AI everywhere. This would take long, be risky, and demotivating both for the Team, seeing no results for months, and Stakeholders. Instead, you should find a simple but tangible use case. Something that can be done in 2-4 weeks and that will show a clear effect (i.e., saving hours per week for a specific Department, speeding up processing of typical requests, etc.).

In discussions about top-down or bottom-up implementation, I always recommend the third way. The ideal scenario is a general strategy and technology stack defined from above (for example, we are building an ecosystem based on Azure AI Foundry), but the first successful case is born «from below», in a specific Business Unit. This case will become a reference that all others will follow. It proves that AI works here, and not just in abstract cases from Vendor presentations.

2. Work with Management as a key link.

You can train ordinary Employees as much as you want. But if their immediate Manager ignores the tool and demands reports «like it was in the last quarter», the implementation will fail. Because it’s more difficult to implement AI in a Department where the Manager is skeptical or indifferent to it. Therefore, working with Line Managers and Directors is not an option, but a prerequisite. The statement of the Company's First Person is crucial here, but it must be supported by the actions of Middle Managers.

3. Create a transparent Company AI Commitment.

This is perhaps one of the most difficult, but also the most important steps. Believe me, your Employees have every right to know what will happen to them next. The fear of losing their jobs due to automation is real and deep. No «AI will not replace anyone; it’s only an assistant» slogans work out if they’re not supported by the official position of the Company.

A public commitment should explain:

• How does the Company see the transformation of roles?
• Are there any plans to reduce Staff? And if so, what reskilling programs are offered?
• How can an Employee influence their career in the face of change?

I haven’t yet met Organizations that would adopt such a document without long discussions and disputes. But those who do remove a huge layer of existential anxiety that prevents People from focusing on work.

4. Create a program of Champions (and not just appoint responsible People).

In every Unit, some grab new things on the fly. i.e., Early Adopters / Champions. Find them. Give them the official status, allocate time for experiments, invest in their training. Make them visible: celebrate, give little but symbolic prizes.
Champions are your bridge between IT and business. They are the ones who help to work out use cases for the specifics of their Department and become the very Colleagues who are not afraid to come to for advice.

5. Reorganize the work of the Support Service.

Users should not feel abandoned. In the first few months of implementation, the Service Desk workload will increase. If Users receive empty replies or delayed responses to their requests, they will no longer return to experimentation with AI. Train your Support Team first. There is a practice of allocating a separate Support Group that would support AI incidents. Or involving the Contractor's Implementation Team, which would help make the start smoother.

6. Create a knowledge library.

No one reads multi-page instructions. Make short guides. Accumulate effective prompts and cases for solving specific tasks. Segment them by business functions and post them where it would be convenient for Employees to access.

Ideally, if in parallel you launch a simple AI bot that will respond to requests for cases, prompts, etc.

7. Arrange training.

You should not limit yourself to one training, like How to use ChatGPT. A series of activities is needed:

• General lectures on what AI really is, what its shortcomings are (yes, about hallucinations, too), how professions in your industry are changing. This removes the fear of the unknown.
• Subject-specific training for each Unit separately. One approach for Legal, another for Marketing, and a different one for Finance. This is where Champions play a key role.
• Clarification of the regulatory framework: dos and don'ts in terms of data security, compliance, intellectual property. When a Person clearly understands the framework, they cease to be afraid of accidentally violating it.

Record these trainings, add them to your knowledge base, add them to the onboarding procedure, index this knowledge with your corporate chatbot. These simple steps will save your Employees a lot of time in the future.

8. Add some drive.

Implementing AI is a major engineering and organizational challenge. But this does not mean that the process should be boring or scary. Competitions for the best prompt, photos with funny generation results, internal AI Fridays are not just entertainment. This is the way to make the technology part of the corporate culture, remove unnecessary seriousness, and let People feel that it is ok to experiment.

9. Implement gradually.

If you have many Departments, it is worth breaking the implementation into waves. But do not split the business function into different waves — the implementation is much more efficient when the Departments get into waves as a whole. Waves will allow you to reduce the cognitive load on Support, work out approaches in more AI-friendly Departments, and make changes to the implementation process based on the experience of previous waves.

10. Measure, measure, measure!

Measure the impact on business processes: how much time the Department saves, how the quality of documentation has changed, whether decisions are made faster. Everyone needs to understand that AI is about value, not about fun. Numbers are perceived very well both from the top and from the very bottom of the hierarchy.

Why will this work out?

Let's go back to our Power User portrait. If we look at each of their traits, we will see that they are covered by specific actions from our plan.

• They're not afraid of AI — because they believe in the Company Commitment, understand the essence of the technology from lectures, and see a successful Quick Win.
• They know the capabilities — thanks to general training pieces, knowledge base, and cases supported by metrics.
• They know how to apply — thanks to subject-specific training pieces and scenarios from Champions.
• They see a real-life example — through the involvement of Management.
• They have the backing — thanks to Champions nearby and well-trained IT Support.
• They're charged with positive energy — through internal marketing and recognition of successes.

It might sound cliché, but once we all learned how to use a phone, then a personal computer, then the Internet. Each of these technologies was equally scary and incomprehensible at the time. Today, we face the next challenge: we need to learn how to use Artificial Intelligence. This will take time. So, if you didn't start yesterday, the best time to start is today.