At Faculty we believe that artificial intelligence (AI) is at its most valuable when it can be applied to the real world, enhancing products, improving services and saving lives. This is only possible with the combination of the right strategy, software and skills, and we are in the unusual position to offer all three elements and in a synergistic way. This is the first in a series of blogs following our new brand launch that explores our unique offering. I’d like to kick off by looking at the importance of skills to building AI capability.

Our academic heritage means that we place great value on education. We care deeply and are proud to play our part in producing the next generation of AI talent. There has never been a more important time to do this. AI has emerged as the most important technology of our time, but having worked with many organisations and leaders, a skills gap is often the top challenge they face.

Building a talent pipeline

We started out in 2014 with the fellowship to help PhD graduates and postdocs in Science, Technology, Engineering and Maths (STEM) transition to become professional data scientists through an eight-week training programme. As part of this, fellows would work on projects for a range of organisations, across multiple different industries.

It was a concept we believed in. What we did not anticipate was how successful it would become. The fellowship is now incredibly competitive and attracts applications from 5–10% of the UK’s postgraduates in physics, maths and engineering from top universities. I often joke that the quality of the applicants is intimidatingly good and if I were to apply, I would not be put through to the next round.

After 13 fellowships, we have helped 250 fellows transition to industry. They have gone on to work at a broad variety of companies, from well-known names such as Google Deepmind to startups such as Deliveroo and non-profits such as the Amnesty International and the Financial Conduct Authority. Many are now senior data scientists, some have become machine learning engineers and some are leading data science teams. We are extremely proud of our alumni and the journey they have gone through.

We have had the privilege of working with more than 130 organisations who have submitted projects and hired from the fellowship. Many of them have built their data science team by participating in the fellowship over the years. We have worked with them closely through hiring as well as sharing our experience in retaining their people. Data scientists are in very high demand, so devising a good strategy for retention is paramount. What organisations don’t want to go through is investing in hiring outstanding talent just to have them leave soon afterwards.  

Building internal capacity at all levels

Building a talent pipeline is only part of the solution. In addition to our fellowship programme, we also help companies to develop up-to-date knowhow and skills within their own data science teams. We do this in different ways, including integrating training into our AI software development work through joint client and Faculty teams. We run specialist training workshops and courses for different roles within the organisations. For example, in 2018, we have delivered AI for executives training to more than 170 senior people in organisations. Our trainers are some of the most accomplished and experienced in the subject matter.

What I have learned through working with training staff from different organisations is that to most effectively address the skills challenge requires thoughtful strategy and planning. My observation is that upskilling the managers and senior people who lead AI effort and teams is crucial in improving the technical proficiency of staff. Without the right leadership and management, it is difficult for the organisation to build and develop AI capability.

I am keen to hear readers’ experience on building AI capability, and in particular addressing their organisations’ skills challenge. In my next blog post, I will share our experience and observations of best practices and pitfalls in building AI skills in organisations. So stay tuned.

If you would like to find out more about our fellowship and how to apply, visit here.

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