£147 million investment into manufacturing
- Steph Organ
- Archive , Blog
- November 9, 2020
- Updated:
Table of Contents
Artificial Intelligence (AI) has been heating up for several years, and the recent challenges imposed by COVID-19 have accelerated efforts to get this tech in the hands of businesses to drive innovation and build agility and resilience. AI has been receiving lots of attention from the UK government and is one of the four Grand Challenge areas in the Industry Strategy.
As part of the 2018 AI Sector Deal, they pledged £1 billion support package to promote the UK’s position as a leader in developing AI and emerging technologies, highlighting that AI has the potential to add £232 billion to the UK economy by 2030, boost productivity in many industries by 30% and generate savings of 25%. In 2019 £18.5 million of this was invested in upskilling 2,500 people through AI and data science master’s conversion degrees.
The UK Government is set to invest £147 million into the Manufacturing Made Smarter Challenge with industry funding topping this up to £300 million. The aim of the challenge is to bring up productivity by 30%, support the adoption of advanced technologies such as AI, increase customer reach and jobs, and reduce carbon emissions and prices. They also want the UK to be an industrial leader, shaping how the world does business by 2030. Recent rounds have had a focus on supply chain innovation, due to the disruption caused by COVID-19.
Digital transformation is a top priority for manufacturers who need to drive productivity, efficiency and innovation in order to stay competitive. As a huge driver of the economy, accounting for around a fifth of the UK’s GDP, the British government is also heavily invested in Artificial Intelligence (AI) and other emerging technology in this industry. Historically, manufacturing has accounted for up to a quarter of GDP in the UK, and has the potential to reach such heights again with the use of new and emerging technologies. Such technologies include:
- Artificial intelligence, machine learning and data analytics
- Additive manufacturing
- Robotics and automation
- Virtual reality and augmented reality
- The Industrial Internet of Things (IIoT) and connectivity.
