Where to Start with AI Implementation: Three Decisions for the Business Owner

Many hear about artificial intelligence (AI) and want to use it for their business, but don't know where to start. The market is flooded with tools, advice, and offers, which can be overwhelming. For AI implementation to succeed, you need a clear plan and an understanding of three key decisions the founder must make.

Why These Three Decisions Matter

Before spending money on software, consultants, or training, a business owner must define the core principles. These three decisions lay the foundation for a future AI implementation strategy and help avoid chaotic experiments that yield no results. They help you focus on real company needs, not just trendy fads.

1. Who Will Own the Automations in the Company?

This is the first and possibly most important decision. You can go the route of contractors who build automations for you. Or you can train your own employees to create them independently. Each approach has pros and cons. If you order every automation externally, first, it's expensive and slow. Second, you become dependent on the contractor who knows how your tools work. But if your people build the automations, they deeply understand business processes and can quickly adapt them to changes. The company of the future is one where every key employee has 10–20 of their own automations, making it flexible and independent.

2. Where to Start: Founder, Key People, or Frontline Staff?

The answer to this question defines the rollout order. Starting with frontline staff can lead to fragmented and ineffective initiatives. The best results come from an approach where the founder or a group of key employees first master AI. They see the potential, understand how it works, and get their own early wins. Only then can you scale training to other employees. This builds internal expertise and sets an example from the top. Such an approach ensures AI becomes part of company culture, not just another tool imposed from outside.

Definition: An AI agent is a program that uses artificial intelligence to perform complex tasks requiring contextual understanding, decision-making, and interaction with other systems, imitating human activity.

3. What to Automate First: Big Processes or Small Routines?

The temptation to immediately automate complex, business-critical processes can be strong. But often this leads to high costs, long timelines, and high risks. Better to start with small, routine tasks that daily "eat up" significant employee work time. These could be report preparation, data gathering, or responses to common inquiries. Quick wins on such tasks let you see real AI benefits, gain experience, build successful cases, and increase trust in new technologies. This is also part of our AI implementation methodology, which assumes gradual expansion of AI tool usage.

Step-by-Step Plan for Decision-Making

To systematize the process, we suggest this plan for the founder:

1. Week 1: Define the Automation Owner.

   • Days 1-2: Discuss with key managers who should be responsible for creating and maintaining automations. Do you have internal resources, or are you planning to hire external specialists? Remember the risks of contractor dependency. Consider training your team so it can create and deploy AI tools independently.
   • Days 3-5: Conduct individual talks with potential "AI champions" in your team. Assess their readiness for training and implementation. These could be technical specialists or managers who deeply understand processes. Consider whether hiring an AI specialist makes sense or training your own team is more effective long-term (see /uk/blog/ai-specialist-vs-team-training-cost-comparison).

2. Week 2: Choose the Target Group for the Start.

   • Days 1-2: List key employees who will have the greatest impact on AI implementation. These could be department heads who own processes needing automation.
   • Days 3-5: Schedule the first training or pilot project specifically with this group. It's important they feel AI's real value and become its ambassadors inside the company. This matches our approach: start with the founder, then key people, then frontline staff who actively want to grow.

3. Week 3: Define the First Tasks for Automation.

   • Days 1-2: Gather data on the most routine and time-consuming tasks in your company. Ask employees which tasks they'd like to "hand over" to AI. As experience shows, the first 3–5 small automations deliver the biggest and fastest results.
   • Days 3-5: Choose 3–5 tasks that are non-critical but time-consuming. Define clear success criteria for each automation. This lets you quickly assess effectiveness and gradually scale AI. For this, our company org chart tool can help: it shows departments, tasks, and routines that can be delegated to AI agents, and even calculates monthly hours. Available at: https://course.aiadvisoryboard.me/uk/orgchart?utm_source=blog&utm_medium=article_body&utm_campaign=orgchart

What Risks Should You Consider?

AI implementation is not just opportunities but also risks. Key ones: lack of clear strategy, dependency on external contractors, employee resistance, unrealistic expectations, and choosing mismatched tools. Often companies spend significant funds on pilot projects with no continuation. To avoid this, you need a clear vision and understanding of how AI will integrate into daily work.

Definition: LLM (Large Language Model) — a large language model; a type of AI trained on massive text datasets, capable of generating text, translating languages, writing various creative content, and answering questions informatively.

Definition: ROI (Return on Investment) — a profitability metric showing the effectiveness of costs and returns from invested funds.

Definition: ChatGPT — a popular LLM model from OpenAI that lets users interact with AI to perform various text tasks.

How to Measure Success?

You can measure AI implementation success not just by cost savings, but also by productivity gains, error reduction, task speed, and employee satisfaction. It's important to set specific, measurable indicators before starting each automation. For example, if automating commercial proposal creation, the success metric would be the time a manager spends preparing them, or the number of proposals they can create per day. Track these metrics to see AI's real impact on your business. Regular meetings and result analysis help adjust strategy and scale successful solutions.

How This Works on Our Side: We offer a corporate intensive for key personnel: 4 live sessions of 2 hours each over 2 weeks for a group of up to 20 employees. The company selects 3 priority tasks, and by program end has at least 3 working automations — with a money-back guarantee. No coding needed: participants describe logic in words, AI writes the code. Result: at least 3 working automations on tasks the company itself defined as priorities. https://course.aiadvisoryboard.me/corporate?utm_source=blog&utm_medium=article_body&utm_campaign=corporate

FAQ

Do I Need Technical Education to Start Implementing AI?

No, a company founder does not need technical education to start implementing AI. What matters is understanding business processes and seeing where AI can help. Even without technical knowledge, you can learn to describe business logic in words, and AI will write the code for automations.

How Long Will Implementing the First Automations Take?

First micro-automations can be launched very quickly. For example, in our sessions, participants launch their first automation in the browser by the second session. For more complex processes, this may take several weeks, depending on complexity and data preparation.

Can Employees Resist AI Implementation?

Yes, resistance can arise from fear of job loss or misunderstanding. It's important to clearly explain AI's benefits, show how it eases routine work without replacing people. Involving employees in choosing automation tasks and training helps reduce resistance.

How to Protect Confidential Data When Working with AI?

For sensitive processes, we use test or anonymized data in sessions. Also, upon request, we can sign a non-disclosure agreement (NDA). It's important to ensure all tools and services comply with your confidentiality policy and are used responsibly.

Conclusion

Adopting the three key decisions — who owns automations, who to train first, and what to automate first — lays a solid foundation for successful AI implementation in your company. Don't start with tools; start with a clear vision and understanding of your own needs. Tomorrow you can take the first step — take a free 30-minute consultation-diagnostic where we'll break down one real task from your company.