Q&A: Aram Lauxtermann on Datacom’s AI strategy

• Datacom’s AI strategy is proven in-house before being delivered to customers.

• Businesses must move beyond pilots to achieve real, measurable AI outcomes.

• Success with AI depends on clear strategy, strong governance and upskilling staff. 

I grew up in the Netherlands, beginning my career at ING Bank working on trading algorithms and innovation projects. After experience in startups, I led KPMG cloud and data practices in Japan.

My daughter was born in Japan. We were travelling a lot, which got us thinking, where do we want to raise her? We really loved Australia, so we eventually moved here after I was able to gain permanent residency for exceptional international achievements.

I joined Avanade, a joint venture of Microsoft and Accenture, where I had various roles including the Australian Chief Technology & Innovation Officer before making the move to Datacom.

It was Datacom’s unique culture, vision for technology and the authenticity of its people that drew me in. After meeting the team, I saw how their approach and values aligned with my passion for long-term customer relationships and genuine technical solutions.

My background is in machine learning and AI, and I was struck by Datacom’s unique approach to making artificial intelligence deliver tangible business value for customers. Take application modernisation. You have a legacy IT estate you want to modernise. Datacom developed a workforce of AI agents to take over and automate integral roles within that process.

Datacom has gotten to a level of maturity in its approach to AI where we can demo this to customers in real-time, an AI workforce of developers, testers and business analysts. It’s real, it delivers and Datacom will do it for a fixed fee, which mitigates the risks that these projects fail or slip. Some customers spend 60 - 80% of their IT budgets supporting legacy systems, so that’s very commercially attractive. 

AI adoption has grown rapidly, but many businesses are still experimenting with pilots and proofs-of-concept and are struggling to see return on investment. Sectors are beginning to move from hype to tangible transformation, but there is a big opportunity for more strategic adoption which is what Datacom can help with.

Datacom is unique because we transformed our own business first using AI. We created an “agentic AI workforce” before applying these innovations to customers. We became customer number zero for our AI agents, applying them in areas like software development, operations and AI practice. So we understand what works. We know this is real, not hype or buzzwords.

We have already created, trained, and improved the entire agent architecture and framework, basically having an agent team that can autonomously produce work, with human oversight. Now we can use that logic to improve customers’ business processes and modernise your IT estate. That approach is truly unique.

By focusing on solutions that can be demoed in real time and delivering fixed outcomes, Datacom avoids "slideware", theoretical, non-working models. Our commercial approach mitigates client risks, making AI real and effective, not just aspirational.

A pitfall is taking a use case approach without a strategic framework, governance and clear key performance indicators that track returns, which often leads to failed pilots and scaling challenges. Many advisers lack both the strategic and technical acumen, resulting in poor guidance and costly errors. That’s where Datacom comes in — we can help organisations avoid those pitfalls. 

Start by defining what success looks like: what you want to achieve, how AI changes your organisation, and what the end-state should be. If you are seeking to transform your company, you should have a framework that accommodates your entire organisation, enabling cross pollination; where finance can learn from marketing’s AI implementation, for example.

Build a strategy with clear and realistic expectations about the value you are seeking to realise, whether automating away costs or boosting revenue, and ensure your technology partner is willing to commit to real, measurable outcomes.

Especially in the public sector, organisations must pay close attention to data sovereignty and regulatory risks, using hybrid or local hosting for sensitive information. For both public and private sectors, workforce awareness of risks, model validation, and compliance with evolving regulations is crucial.

Most of us work with AI as an assistant for regular tasks. But people in the organisation need to be trained to work with data, know how to validate hypotheses, identify bias and hallucinations. How do you verify that the thought chain and results are correct? Datacom’s extensive experience in the public sector, where regulatory compliance is comparatively high, has made us adept at helping customers put in place the governance and guardrails that allow them to move fast and innovate safely.

AI is making routine tasks easier, but organisations must invest in tailored training that empowers every employee, not just data scientists or IT staff, to work effectively with AI systems and spot errors or hallucinations.

Part of your framework for AI has to account for how people’s jobs will change as it is adopted, and how you support those people to assume higher value roles as aspects of work are automated.

With AI, we will all have the ability to augment ourselves with a team of PhDs around us, and that will allow us to learn things about our craft that we were never able to learn before. The future is a highly capable, collaborative workforce natively skilled in AI.

Those who get strategic advice and invest in real, scalable AI solutions will see massive productivity and competitive gains, fundamentally changing how work is done in every sector.

The risk is being swayed by the appeal of impressive AI presentations that have not productionised. Success will belong to those who rapidly iterate, embrace continuous learning, and leverage AI as a genuine enabler of human capability, automation and transformation.