As consumer-facing AI tools have rocketed to popularity over the past two years, innovation is now suddenly at everyone’s fingertips and no longer just reserved for industry experts and academics. To say that this development has been groundbreaking would be an understatement.

Unlike previous technological advancements that quickly fizzled out like any other fad – remember when everyone thought 3D TVs would be the next big thing? – generative AI has already irreversibly changed our lives and the economy. McKinsey Global Institute has predicted that AI will increase the global economy by a value of $2.6 to $4.4 trillion. That’s less of a drop in the ocean and more of a tidal wave. Elsewhere, McKinsey also estimates that generative AI could be used to automate half of all work by as early as 2024. 

It would be easy to panic at that prediction, but like with any other major technological development, change cannot be avoided so it must be embraced.

We set out to help businesses do just that through our Innovation Roundtable series, which brings together industry experts, senior leaders, and decision-makers in organisations looking to innovate by implementing the latest technologies with maximum effect.

To that end, last week, we hosted our first enlightening roundtable with leaders from some of the North West’s most influential organisations.

The guestlist included leaders from The BBC, JLR, Peak AI, Fuzzy Labs, Cegedim Health, Rezzil, Frasers Group and Northcoders. 

On the agenda? Innovation. 

Innovation is a broad term that means different things to different people. But while innovation was the core focus, the obvious diversion to common themes began to develop. 

We set the tone to explore the burning questions that organisations have about Innovation and how they can leverage new technologies, methodologies, and processes to drive growth and learn from peers about the incredible innovation they’re experiencing. 

Among some other interesting discussion topics, as expected in the current climate, we delved into the transformative potential (and challenges) of generative AI and large language models (LLMs) being brought into core business practices. 

The session, co-hosted by AI industry experts Robbie (Fuzzy Labs) and Tom (Peak AI), was rich with insights, focusing on practical applications, innovation strategies, and future-oriented thinking.

Setting the scene for our roundtable discussion

In the beautiful setting of 20 Stories overlooking Manchester’s expanding skyline, we opened the floor with key prompts that set the stage for the discussions. Before the event, we prompted everyone to bring thinking to the table based on the following questions:

• What does innovation mean to you and your business?
• What are the major innovations in your industry at the moment?
• What innovation plans do you have for 2024?
• What are your biggest challenges in driving innovation internally?
• Are there specific topics or areas of innovation you’re keen to explore in this roundtable?

What we learnt from each other 

Firstly, we opened the floor with insights and scene setters from Robbie and Tom, establishing a core foundation for the wider discussion. 

Soon after, our conversations centred on how businesses can harness LLMs and AI to conceive, develop, scale products or services and, above all else, improve operational efficiencies. 

A consistent theme that emerged was the importance of adopting a purposeful approach to innovation, leveraging innovation and especially AI to address actual, specific business challenges and fostering a problem-solving mindset over merely adopting the technology for its own sake. 

Whilst much of the information remains sensitive in the Roundtable sessions, so we can learn from one another through open dialogue, the key themes have been condensed below:

The need for strategic adoption with purpose 

A consensus emerged on the importance of starting with efficiency improvements as a primary objective for AI adoption. Attendees stressed the need for organisations to adopt a strategic, goal-oriented approach to change, leveraging methods such as Objectives and Key Results (OKRs) to track results. 

According to recent studies, businesses that strategically implement AI initiatives see a 51% improvement in operational efficiency on average (source: Deloitte). Additionally, it was highlighted that retrofitting a strategy around a product or service without a clear business case can lead to failure, with around 87% of AI projects failing to make it to production (source: Gartner).

The AI talent gap

Despite the availability of skilled technology professionals in the market, there remains a significant shortage of data scientists to meet the growing demands for data-driven AI solutions. Recent reports suggest that by 2025, the demand for data scientists and AI specialists will exceed supply by 50% (source: World Economic Forum). 

Addressing this talent gap through internal training and development programs is crucial for organisations looking to harness the power of AI effectively and leveraging organisations such as Northcoders to train and retrain talent is a strategic advantage.

But closing the AI talent gap will need to be a well-thought out process. The World Economic Forum reported that women account for only 22% of AI roles and as the wider tech industry has proven, when it comes to meeting the demands of the sector, decision makers need to embrace diversity in order to train, retrain, or hire the significant number of skilled people required.

Understanding and leveraging AI

Deepening stakeholders’ understanding of AI and dispelling misconceptions emerged as a key priority. Research shows that only 33% of business leaders have a good understanding of AI and its implications for their organisations (source: PwC). 

By educating stakeholders and focusing on practical applications, businesses can unlock the full potential of AI for process improvements and business transformation.

Ethical and practical challenges

The discussion delved into critical ethical considerations surrounding AI, including intellectual property creation and regulatory compliance. With the rise of AI-powered content generation tools, concerns about plagiarism and ethical use are more pertinent than ever. Additionally, navigating regulatory frameworks such as GDPR and ensuring compliance with ethical guidelines are essential for responsible AI deployment. Are we just trying to shut the door after the horse has bolted? Should we be embracing a more open-source future with ownership?

Sustainable thinking and CSR

Participants highlighted the urgent need to address the environmental impact of data consumption and advocated for adopting greener technologies. Research indicates that data centres account for about 1% of global electricity demand, with projections showing a significant increase in energy consumption due to data growth (source: Nature). 

Despite the report co-authored by Google last year that stated AI has the potential to cut global carbon emissions by as much as 10%, the fear is that this power-hungry technology will do just the opposite. And these fears aren’t unfounded. We already know that training ChatGPT requires the same energy usage as what 120 US households would consumer over the course of a year.

Embracing sustainable practices such as green data centres will help reduce the carbon footprint of AI and data-driven technologies. But how quickly can we switch and solve the problem?

Innovative thinking & training

Fostering a culture of innovative thinking and investing in training programs emerged as critical strategies for addressing complex technical challenges. Research suggests that businesses with a strong focus on innovation training are 1.5 times more likely to outperform their peers (source: Boston Consulting Group). 

Organisations can drive meaningful innovation and stay ahead in the competitive AI landscape by equipping employees with the skills to leverage off-the-shelf tools and solve complex problems.

Our event provided valuable insights and actionable strategies for businesses looking to navigate the complexities of AI adoption and innovation, ensuring they are well-equipped to drive meaningful change and stay ahead in today’s rapidly evolving digital landscape.

Future thinking

Looking ahead, the conversation underscored the need for companies to navigate the AI landscape with a conscious, problem-solving approach, focusing on areas where AI can offer significant value, like efficiency and innovation. 

The role of internal champions in driving innovative thinking and AI adoption, the importance of data and customer insights, and the potential for AI to revolutionise industries were highlighted as critical factors for future success.

Taking this forward

The roundtable was a clear call to action for businesses to critically evaluate and strategically implement AI technologies. Companies can navigate the evolving technological landscape with confidence and foresight by focusing on purpose-driven innovation and ethical considerations and leveraging AI for genuine problem-solving.

Through our Innovation Labs, we work with organisations to leverage their data and the latest technologies to create better customer experiences and internal efficiencies. Innovative thinking is a crucial part of this. We designed this cutting-edge offering to empower our clients with the latest technological advancements. The Innovation Labs allow you to harness the full potential of bleeding-edge technologies like LLMs, AI, AR, connected devices, IoT, and other deep, immersive technologies.

We’ve introduced innovation roundtables, which allow our clients to go through our methodology and help them unlock an understanding of how to move their business forward with the systems they already have in place.