Article
5 minutes read
Joe Dunleavy and Seth Clifford

When we began our generative AI journey inside Endava, we swiftly recognised that beyond technology, fundamental philosophical questions were raised as well. The more we probed into the problems we wanted to solve and the reasons behind them, the more we realised certain universal themes that resonated with many of us.

 

What do you do?

 

What does ‘work’ mean? What are the things you do every day that define your concept of ‘work’?

 

Is the myriad of documents you read and process the core of what you do? What about the unending emails, chat messages, phone calls, meetings and general discussions you have? Is that your 'work’? Do these activities signify your purpose?

 

May we be so bold as to say, probably not?

 

What we do and what we think we do are two vastly different things. The mechanics of how we spend our days are mired in so many tasks that consume time, energy and emotion. We all want what we do to have meaning. And yet, so much of what we do feels like it doesn’t. It feels like swimming upstream against a strong tide, never getting to the real things that matter or can make a valuable difference in our job satisfaction or our company’s performance.

 

The unexpected removal of constraints

 

This naturally led us to a question: what is fundamentally different about the world of today and the world of tomorrow with AI as a part of it?

 

Work as we know is predicated on three major factors: cost, time and scope. These are the constraints we face when doing just about any project. “Pick two”, we’re told. You can’t have all of these because people have limits, time isn’t infinite and your budget is never as large as you would like it to be.

 

But what does a project look like when those three core constraints no longer matter? How do we envision what we can achieve when we remove the entire notion of constraints? If AI can truly support what it promises – work faster, cheaper and without limiting our vision – what more could we accomplish in our daily work?

 

The importance of building trust

 

There’s an element of working with AI that naturally creates a sense of unease, particularly for mission-critical tasks. To do real work in the real world, we need to build trust in our systems, which presents a challenge when everything is new and moving so quickly. The experience of not being able to see inside this ‘black box’ naturally leads to distrust.

 

But what if we look at it from another perspective?

 

If you hire someone new to your team, you review their work to ensure correctness. Once you’ve spent time working with someone who has performed well and gained your trust, chances are you’re not taking that step anymore because you know they’re doing it right. We follow processes to ensure predictable outcomes for success.

 

Those same processes should be applied to AI to create trust. Over time, it learns what you’re looking for and provides more consistent and predictable results. This isn’t alchemy; it’s a familiar process to us all – with minor adjustments.

 

A new model of interaction

 

Okay, but what is it about large language models and generative AI that makes what we’re talking about so novel and different from all that came before it?

 

It’s surprisingly simple.

 

Since the dawn of computing, humans have had to invent ways of communicating with machines. From punch cards to Fortran, to BASIC, to JavaScript. And so on.

 

We’ve always had to create an abstraction layer – a way to translate our thoughts into code that was readable by the machines we created. When we wanted to communicate our ideas to the people around us, we simply spoke to them in our natural language.

 

We invented entire foreign languages to speak to computers because they couldn’t understand our most natural means of verbal expression. We couldn’t talk directly to them, and they couldn’t talk back to us.

 

With the rise of large language models, now they can.

 

Enhancing the human potential

 

With these ideas and discussions in mind, we’ve been working on the launch of our innovative agentic AI industry accelerator, that we internally call Morpheus. Our first-of-its-kind solution and its AI-powered industry tools combine the power of data and multi-agent autonomous teams to tackle complex challenges across all industries, including highly regulated fields like healthcare, financial services, insurance and private equity.

 

We see these tools helping our clients to create space in the day to focus on truly valuable activities, becoming more productive and delivering incredible new value. Now that we have the scene set, we invite you to dive in and learn more about the new era of autonomous agents and how taking AI out of the ‘black box’ is marking a new era of possibilities.

 

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