MyM Consultancy

About us

We help organizations figure out where AI genuinely solves problems. We’re not here to sell you AI for its own sake. Instead, we work with you to identify real opportunities, build practical workflows, train your team to use them effectively and stick around to make sure they work. We believe AI is a tool for people, not a replacement for them. Our focus is always on how your team works: making their jobs easier, reducing tedious tasks and unlocking new possibilities.

Marko Mitrovic

Marko has spent a decade in IT helping build things that work – from apps to AI systems – and has a clear sense of what are the actual opportunities versus where the hype runs ahead of reality. His hands-on experience spans AI agent development, designing no-code tools, AI systems architecture and prompt engineering that underpins it all.

Marko’s educational foundation in economics gives him a lens on how technology creates value, he is not just thinking about what is technically possible, but what is actually useful. His real interest is understanding where AI can meaningfully improve the way people work and bridging the gap between technical depth and business reality.

Marija Ignjatijevic

Marija comes from ten years of research, project management and experience in designing and coordinating training and mentoring programmes. She translated this background directly into AI work and has developed materials and facilitated workshops to try to make complex AI topics accessible to non-technical audiences.

With a degree in political science, she is interested in the bigger picture: the evolving AI regulatory landscape, privacy considerations and the social trade-offs that often get skipped in technical conversations. She sees AI as a tool in the service of people, which means exploring where it can deliver and where it falls short.

Frequently asked questions

It’s not too soon. The tools are mature enough now that any team willing to learn can get real value – this isn’t bleeding-edge technology anymore. Readiness is less about your company and more about two things: are there repetitive tasks you actually want to offload, and does your team have the headspace to learn something new for a few weeks? If yes to both, you’re ready. If not, start smaller – one person, one task. An AI expert can help assess where your team is and pick a starting point that fits.

An AI consultant looks at how your business runs, identifies where AI can genuinely help (and where it can’t), picks the right tools for your situation, and trains your team to use them well. The role sits between business and tech – less about building AI from scratch, more about fitting existing AI tools to your workflows, your data, and the people who’ll use them. The best ones stay involved after setup, so when your team hits rough patches or the landscape shifts, someone who knows your stack is there.

For most SMBs, outsourcing makes more sense than hiring. AI projects are front-heavy – a lot of work to scope, pick tools, design workflows, and train people – then relatively quiet once things are running. Paying a full-time AI specialist to sit through the quiet phase is expensive. Bringing in a consultant for the intense early months and keeping a lighter retainer afterwards usually works better. Hiring internally pays off only if you’re at a scale where AI changes constantly, or you’re already a software company with technical depth on the team.

It depends on how much AI work you expect steadily. A consultant is better when AI is a project or a new capability – heavy lift for a few months, then lighter. They bring breadth: they’ve seen other companies, know the current tool landscape, and won’t reinvent the wheel. An in-house specialist makes sense when AI is woven into how your product or operations run and needs constant development – you’d pay for them to be idle half the time with a consultant model. For most companies that aren’t AI-native, the consultant-plus-internal-champion setup beats either extreme.

A developer builds software – they write code to create custom applications or integrate systems. An AI consultant shapes what gets built and why, picking existing AI tools, designing the workflow around them, training the team, and deciding where humans versus AI fit in. There’s overlap – some consultants code, some developers understand AI deeply – but the roles answer different questions. A developer answers ‘how do we build this?’. A consultant answers ‘should we build this and what does success actually look like?’.

A typical engagement covers four areas. Assessment – understanding how your business runs, where AI fits, and what’s worth tackling first. Solution design – picking tools, designing the workflows, handling data preparation and security. Implementation and training – building the flows, integrating with your systems, teaching your team to use them well. Ongoing advisory – check-ins to monitor quality, adapt as tools change, and guide the next round of adoption. Not every company needs every piece – good consultants scope to what you actually need rather than selling the full menu.

A few signals separate the good ones from the rest. Tool-agnostic advice – they should recommend what fits your problem, not what they resell. Case studies in your industry or a similar one, with specific outcomes not vague claims. Comfort saying ‘this isn’t a good fit for AI’ – honest scoping matters more than selling the biggest possible project. A clear handoff plan – they should make your team capable, not dependent. And finally, someone who asks sharp questions about your business in the first conversation. If they’re selling before they understand, walk away.

Yes – a good AI consultant handles the technical layer so your team focuses on adoption, process, and results. Most SMBs getting value from AI don’t have an IT department. They have a consultant who picks tools, sets up workflows, handles integrations, and then trains the team to use and maintain what was built. The handover matters: by the end, your team should be able to use and extend the setup without calling for every small change. If a consultant wants to stay essential to basic operations, that’s a red flag. An AI expert focused on enabling your team is the one you want.

Yes, and for most SMBs that’s the right fit. Look for consultants who lead with business outcomes and change management rather than model names and technical jargon. Signs you’re in the right conversation: they explain things in plain language, they ask about your team’s comfort level with new tools, they scope training as part of the engagement (not an afterthought), and their case studies show non-technical teams using the setups afterwards. Consultants who talk mostly to engineering leaders or default to technical language often aren’t the best match for a non-technical team, even if they’re excellent on the tech side.