11 Jan

Life at Mesh-AI: Interview with David Bartram-Shaw, Chief AI Officer

DBS
David Bartram-Shaw

David Bartram-Shaw recently joined Mesh-AI as Chief AI Officer.

We sat down with him to talk about his background in Data and Artificial Intelligence and how enterprises can ensure the successful adoption of AI solutions in their businesses today.

Tell us a bit about your background?

From the very beginning of my career I’ve been interested in changing the way large organisations extract value from Data and Machine Learning.

My journey towards AI started about 10 years ago when I spotted an opportunity for more sophisticated ML solutions with larger-scale impact within organisations.

Since then, I’ve worked across many industries and with many clients, conceptualising, building and delivering projects that move the needle using AI.

While my passion has always been on the algorithmic side of AI, in order to actually deliver impact I have found that there needs to be just as much focus on the technological side — from data engineering to software engineering to end-to-end orchestration.

Of course, data itself is central to this, and is crucial in maintaining a comprehensive viewpoint of the entire ecosystem and in building products. This for me, is how we scale adoption.

What is your role at Mesh-AI?

I’m the Chief AI Officer, which means I'm responsible for developing and delivering an AI strategy across our business and for our clients.

Mesh-AI already has a huge number of incredible developers, consultants and technologists who are delivering game-changing solutions for large enterprises. And the approach to AI enablement here at Mesh-AI, truly sets it aside from any other consultancy out there right now — delivering technology and data platform solutions that provide long term foundations for AI.

My role is to build on this and take us to the next level in terms of our AI capabilities and strategy, across a variety of AI areas. Providing innovations across key client sectors as well as overseeing the delivery of high quality, large scale impact AI solutions.

As we grow, I will be building out our AI Lab: a top-tier pool of talent, innovations and capabilities focused on AI. I’ll also be working directly with our clients to help them define world-class Data & AI strategies and ensure that we deliver in a way that empowers them internally to deliver true AI Transformation.

What interests you about AI?

If I had to distil my interest in AI down to one thing it would have to be AI’s ability to consume data — any type of data — and produce outputs and predictions that help make us better as humans. In this, we should view AI as an enabler.

AI can detect cancer from images, reduce climate control through energy efficiencies, mitigate the spread of forestry disease using drone shots and optimise emergency routes. AI has the potential to enhance (and save) our lives and we are developing the algorithms and technologies that power AI at such a rate that the exciting part is that we get the opportunity to apply these developments to increasingly interesting and impactful applications.

How can enterprises enable successful AI adoption?

First and foremost, you need to have the right data and technology in place so that your AI solutions can scale — as having the right data in place will ensure your AI can learn. Therefore a strong, business wide data strategy is required.

Recently, there has been a rise in the popularity of Data-Centric AI and it is for good reason — it’s a movement that puts more focus on the depth, breadth and quality of data you feed into your models, since it will have a much greater impact on performance vs algorithm testing alone. The technology used to house and distribute this data, as well as train and deploy your AI, is equally as important.

You also need to ensure you have alignment with the business goals of the organisation alongside a deep understanding of what AI can do. This will ensure you are making investments in the right places and building in the right way iteratively.

Finally, and I think this piece is often overlooked, is the need for cultural and organisational change. In the future, AI will be so deeply embedded into every aspect of every organisation that it’s imperative the entire workforce is aligned behind it.

What’s holding enterprises back from AI adoption?

There have been huge investments in AI in recent years, but for the vast majority of businesses, there is still a big gap between the level of investment and the level of impact. There are many reasons for this but at its core I believe this is because organisations are trying to find silver-bullet solutions without changing the foundations of their business.

It’s a little bit like the digital revolution, where the brick-and-mortar market leaders — like Walmart and Blockbuster — thought building a website would do the trick as opposed to changing their entire business to be built on and around this new technology (enter Amazon and Netflix).

A large number of organisations invest in setting up siloed AI teams or throw money at AI-powered software and fail to see long lasting business impact as a result. Impact that can be built on and evolve with the needs of the business.

This is because at its core, AI is only possible with the right data and technology. Both in terms of AI that you can embed into your products or indeed power insights and decisions made by the experts in your business. Therefore you must invest in the foundational infrastructure, skills and strategy to embed AI as a part of your wider organisation.

Finally, AI can often be the elephant in the room. With so much hype, scepticism and confusion, it can be difficult to integrate into the existing business setup for longer term success. This can be solved by building the right culture (grounded in an aligned view on what AI actually is).

From there, you need people who can explain without confusion and who are capable of working with the entire business in the generation of ideas and in the shaping of opportunities for AI impact.

So why did you join Mesh-AI?

Mesh-AI is built on foundations that are all pointed towards AI enablement with an approach that focuses on technology, people and outcomes.

From a technology perspective, this means that AI is not just a small POC that works in isolation, but instead is built into the technological foundations, making it scalable and generalisable to the wider business.

From a people perspective, Mesh-AI’s long term goal is to enable clients to develop and deploy AI themselves. This means building for the future. If we enable clients to become proficient in the use of AI themselves, with the right technological foundations, then we can partner towards game-changing innovations and deployments together. After all, we’ve seen that collaboration is what’s driven such rapid developments in the field of AI.

From an outcomes perspective Mesh-AI starts each engagement by asking, “What business problems are you trying to solve?”, rather than walking in with a menu of “game-changing AI solutions”. Turning the relationship into a collaborative one where the relevant ideas and experts can be brought to the table to answer the relevant business needs.

By building out real proof points that have actual business outcomes in a way that is both iterative (from a technology design perspective) and forward facing (from a generalisable framework and organisational perspective) Mesh-AI provides me the perfect platform to work with clients on game-changing AI.

If you’re interested in joining the Mesh-AI team - we’re hiring! Get in touch with us at careers@mesh-ai.com or find our open roles here.


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