How AI is Improving Innovation

The AI Landscape

“AI may serve as a new general-purpose 'method of invention' that can reshape the nature of the innovation process and the organisation of R&D.” - Nesta

Artificial Intelligence (AI) is revolutionising our healthcare, education and transport industries. It’s improving our infrastructure, our progress towards Net Zero, our cyber security measures and our creativity. 

And it's reinventing the way we invent. 

Let’s take it back to basics: AI is a type of technology that enables computers to think, learn and perform tasks, like humans. Using algorithms, AI takes large amounts of data, analyses it for patterns and trends and then turns that analysis into educated conclusions, predictions and forecasts that allow us to make better, more informed decisions, quicker than ever before. 

The fundamental goal of AI is to complete tasks that traditionally needed human intelligence.

Take medical diagnosis, for example. With AI-powered systems, it’s now possible to combine patient records with medical research and genetic data to find correlations that would normally take Doctors months to find, if ever. It’s the pathway to quicker diagnosis, better treatment, individualised patient care and increased life longevity.

And the same applies to applying for R&D tax credits. For instance, Tax Cloud, the industry's first self-service R&D tax credit platform, allows you to claim the maximum amount of R&D tax relief without having to pay for an R&D tax credit specialist. All you do is describe your R&D activities, add your costs and a machine does the rest. Once you’ve completed the process, your application then gets reviewed by an R&D tax specialist, to make sure you get the maximum amount possible from the Government. It speeds up the traditionally lengthy R&D claim process and reduces errors. Book a demo and see for yourself how quick and easy claiming for R&D tax credits can be.

Innovators and inventors that utilise AI will progress further, and outshine those who bury their heads and continue to do what they’ve always done. 

How? Why? 

Keep reading to find out…

How & Why AI is Improving Innovation

AI makes the testing of innovative ideas quicker, easier and cheaper

“AI is paving the way to low-cost experimentation, thereby accelerating innovation.” - Forbes

Testing prototypes or concepts involves gathering, analysing and combining huge amounts of data, from multiple sources, to establish a sound proof of concept. This has traditionally taken months, if not years, which not only costs a fortune but drastically slows the pace of innovation. 

AI automates repetitive tasks, like data entry and quality control. These are typically manual, time-consuming tasks that are prone to human error, meaning results are often skewed and unusable. 

Using natural language processing (NLP), sentiment analysis and recommendation systems, AI systems collect, organise, combine and interpret colossal amounts of data–from sources like in-field data, research literature, customer feedback, and market trends–accurately and efficiently. This gives accurate insights into opportunities and gaps in research, and a quicker route to clear hypotheses, at a much lower cost.

AI assists with innovative ideation processes

Continuing in a similar vein, as we’ve just discussed: AI-powered tools can analyse vast amounts of internally and externally sourced data, providing us with expertise and insights that would normally take us, mere mortals, much longer to gather and process. This broadens our perspectives and helps us come up with new solutions to complex problems and inspiring ideas that challenge the norm. 

But, AI can’t do it all. Yes, it’s a fantastic tool for ideation, but it needs humanistic consideration to decide which ideas to run with and when to run with them. AI isn’t at the stage where it can factor-in potential adverse effects (like ethics and diversity) and turn ideas into reality. Yet. But watch this space: It’s coming.

AI enables better, rapid decision-making throughout the innovation process

It goes without saying, largely because we’ve already said it: AI can accurately process and analyse a sea of data to find patterns that help inform decisions and enable more effective choices. But again, we still need ‘a little human touch’ (to quote Bruce Springsteen). 

Sure, AI can spot correlations across thousands of data points, and it can suggest solutions that we might never have considered, but it doesn’t have human-like cognition to keep decisions in perspective. 

There is a caveat that comes with AI, though...

A key point, that spans across all three of the above elements, is: to be effective, AI requires a lot of data. And I mean a lot. And it needs to be clean, good quality data that’s accurate, complete and free from bias to avoid misleading predictions and decisions. 

This might be the stumbling block for a lot of innovators and entrepreneurs. There are tools that can help, but this could limit their ability to be truly innovative. 

How Innovators are Using AI in Their Innovations, Right Now

At the beginning of this, we touched on how AI is advancing medical diagnosis. Let’s dig a little more into how other innovators are utilising AI in their fields, right now. 

Self-Driving Technology

Waymo, a technology division of Alphabet (Google’s parent company) is focused on bringing self-driving technology to the masses to reduce the number of crashes. Right now, its self-driving taxis are shuttling passengers all over California as part of a pilot scheme. Even though they can’t charge fares and they still need a human driver to sit behind the wheel, they’ve committed to using AI–in particular, deep learning techniques–throughout their innovation processes. Why else would they have purchased ‘DeepMind’, an AI research lab? 

Personalised Customer Experiences & Inventory, Logistics & Location Management

Starbucks were way ahead of the curve when it came to collecting vast amounts of data: They started in 2011 when they launched their customer-facing app. It helped them understand what products and locations their customers liked, and when they visited their stores the most. Eight years later, armed with reams of data, they developed Deep Brew, their AI platform. Deep Brew uses data to personalise customer experiences, allowing Starbucks to forge deeper connections with its customers. It optimises store opening times and staff needs to make sure all stores are fully staffed and efficiently run. It also manages stock inventory to make sure customers' favourites are always in stock. Not only that, but Deep Brew also helps Starbucks choose their next store location: It analyses location variables like income levels, traffic patterns, competitors and revenue potential to find the best spots with the highest growth potential.

R&D Patent Applications

This is an interesting one: DABUS (Device for the Autonomous Bootstrapping of Unified Sentience) is an AI system created by Dr Stephen Thaler. It created an improved food container that can change shape using fractal geometry. Dr Thaler submitted several R&D patent applications for the invention, naming ‘AI’ as the inventor. Although the UK, EU, and the US rejected granting inventorship to an AI machine, claiming the inventor must be a human, South Africa became the first country to accept AI as an inventor. So this could be the future of R&D patents, and possibly R&D grant applications too. 

For now, if you need support with a grant application, companies wih exceptional grant success like Myriad Associates can help. They can help you prepare an award winning grant application for your next, AI-driven innovative project. 

The opportunities to innovate with AI are limitless. 

Get in touch

If you would like to discuss any aspect of R&D Tax Credits or the Tax Cloud portal, feel free to contact our friendly expert team on 020 7360 4437 or send us a message.

Author Barrie Dowsett, ACMA, GCMA CEO, Tax Cloud