Early adopters? Or smart evolvers?

We guarantee you already know someone who’s using ‘AI’ to make their life a little bit easier.

Not revolutionising their job; not creating a billion-dollar business. Just a hack that makes writing a job proposal a bit quicker, or simplifies a workflow.

That person is our hero.

You also know someone – probably a few people – who throw their LLM of choice at every problem in their life, from pulling together a PowerPoint presentation in HR, to writing the eulogy for dearly departed Aunt Louise, to churning out a new health & safety policy.

They’re like businesses where the hype has seduced people into seeing AI as the solution to every problem. (What they hear a lot on their IT projects is, “well, no, it can’t do what you need yet, but it will blow you away in 18 months, so keep investing…”)

Sometimes, it’s not even a case of seduction. The fear they will miss out on an AI revolution pushes people to invest in any solution that consultancies and IT companies offer. The more extravagant the claims, the more FOMO it creates.

So what makes our hero different? First, they’re focused on outcomes, not processes or technology. An LLM (or any other AI) is just a tool the achieve that outcome. Second, they are in control. They’re not giving up their process to a ‘black box’ system and hoping for the best. They know what they want and how to use the right tech to get it. Third, they’re not sitting on the sidelines. They’re engaged, but not wasting energy.

And that’s magentIQ.

It’s all about agency

We called our company ‘magentIQ’ to reflect the importance we place on that sense of control. When you have ‘agency’, you are directing things, not subject to external forces. And when you have an agent at your disposal, they do what you tell them – they deliver the outcomes you want.

Equally important, an agent works alongside others to achieve that outcome. That’s important, because the application of AI today is not a revolution – it’s never going to be about one company’s latest offering taking over your business. Practical AI is the evolution of tools that we’ve always had.

It’s about a multi-agent workforce that’s tailored to your organisation.

The right tool for the job

It’s not just the company name that frames our thinking here. We’ve been on a journey. We started out working on enterprise resource planning (ERP) solutions. The premise was simple: connect data, people, and processes across an organization to increase efficiency and transparency.

The next place we landed was business process outsourcing (BPO). We saw that most organizations were running processes that would benefit from specialization. Centers of excellence, in places where labor costs were lower, was a logical next step.

When robotic process automation (RPA) emerged in the 2010s, we could take it a step further – bringing even greater efficiency to the interactions between systems within the ERP workflow that included shared service centers and the agents inside them.

ERP still does a lot of heavy lifting. Human agents in BPO centers of excellence (and, of course, within organizations) still contribute hugely to efficiency… and are adaptable and creative. And RPA is delivering enhanced connectivity and efficiency between them all, often via cloud apps and software as a service (SaaS).

Successful approaches have always deployed these ideas in the service of the organisation’s processes, purpose and profit. People were always at the core of the offer. When you look at it that way, none of these three-letter acronyms were a revolution. They’ve all been part of a continuum that’s focused new ideas on process optimization towards clear outputs.

So when people promise that LLMs and other AI technologies will completely upend entire business models, we’re sceptical. We don’t treat AI any differently: it’s another tool on that continuum, an agent that sits alongside the others in your organization. It can take us – you – on the next stage of that journey.

To be a pragmatic futurist is to be attached to history. The way we deploy AI must respect where our organizations have come from, and offer them opportunities to continue evolving when the next tech shift happens. We think lots people running businesses that can’t afford to bet millions on a risky revolution would agree.