AI is a rapidly evolving digital landscape, continuously opening up new possibilities in engineering. It’s enhancing productivity, optimising supply chains and driving innovation.
In fact, recent figures suggest it has the potential to increase GDP by up to 10.3% by 2030, the equivalent of £232 billion[1]. So, it’s no surprise that a £7.4m Flexible AI Upskilling Fund pilot scheme was set up to subsidise the costs of AI skills training for SMEs. It’s clear that in order to truly realise the potential of AI adoption, we must ensure that SMEs are brought on this journey – not left behind.
There are three significant opportunities that will undoubtably aid this mission: effective support systems, adequate training around AI and facilitating the continued digitalisation of the engineering and manufacturing industries.
Small steps, big impact: unlocking AI potential
If we first take a closer look at SMEs – by nature these businesses operate on a smaller scale, with lower capital and a smaller workforce too. This tends to limit investment in machinery and infrastructure, which in turn means a reliance on labour-intensive techniques that involve less automation.
By providing more practical support and advice around the adoption of digital technologies, including AI in particular, the initial time and investment needed can be reduced for SMEs to explore and implement the capabilities of AI.
This will help to build trust around AI systems – at all levels of the organisation – and break down any barriers to its adoption. This can include guidance on the changing regulatory landscape, which funding options are available, as well as how businesses can access vital support.
Lessons from the leaders
Further to this, a key area where SMEs often require support is the development of AI strategies. Larger businesses, who have invested significant time and resource into developing these strategies, are best placed to share guidance on lessons learned.
What’s more, access to cutting edge facilities and support from and support from The Catapult Network also provide companies with the right expertise and low risk environments to push boundaries and innovate.
This will allow more SMEs to benefit from lessons in best practice and eliminate the need to invest time and resources in developing the processes from scratch.
Digital transformation: an SME roadmap
Digital transformation is the backbone of adopting AI systems in engineering. However, a lack of appropriate digital skills, infrastructure and processes – which are typically the challenges that SMEs face – can act as significant roadblocks to success.
For organisations at the start of the digitalisation journey, setting out the aspirations, challenges and opportunities associated with digital transformation is a great place to begin. For this discovery phase, there’s a wealth of expertise available through technology suppliers, academic institutions, as well as the Catapult Network.
Planning is also a vital piece of the puzzle. It helps organisations create a roadmap for success by identifying strategic focuses and the technology required to support this journey.
After that, organisations can move into the design and build phase: put simply, this process virtually validates the concept, helping organisations to build processes using standard, modular and automated zones. Finally, through remote monitoring, quality assurance and production optimisation, SMEs can streamline and optimise the process for the future.
Empowering AI in SMEs: training for success
Underpinning all of this is the people actually using AI systems and driving digital transformation forward. Ensuring they have access to relevant training is fundamental, including SME leaders and those in C-suite positions, who need to be acutely aware of the potential risks and opportunities of any disruptive technologies, such as AI systems. This knowledge can then be filtered right the way through the organisation.
Those operating AI systems also require upskilling and reskilling on relevant programming languages, machine learning frameworks, data handling and cloud platforms. What’s more, training on AI governance, best practice, ethics and regulatory compliance are all essential, ensuring that the entire workforce has the right skills to implement AI and help the business to thrive.
Ultimately, this support will help smaller engineering and manufacturing businesses to innovate, automate and optimise in a way that wouldn’t have been possible without the effective use of AI. The potential impact on the wider industry is great – after all, innovation is the engine for manufacturing, helping to unlock investment and growth.
Dr Nandini Chakravorti is Associate Director, Digital Engineering at The Manufacturing Technology Centre
[1] Gov.uk (March 2024)
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