The transformational potential of AI - a new perspective

The summit celebrated its 8th year as an industry leader, showcasing the latest innovations and practical applications of AI, as well as commercial use cases that delivered telling insights.

As we set the agenda for the next 12 months of digital transformation, the summit provided the perfect platform to review the hottest topics and trends paving the way for AI success. Whilst Generative AI is still at the forefront of many conversations, as AI moves from theoretical conversions to strategies around implementation and commercialisation, the focus has no doubt shifted focus to how to manage AI in a business setting, the ethical and responsible considerations, the impact on security and measures to put in place, as well KPIs on measuring success, ROI and investment opportunities when building out your tech stack.

We asked our attendees to share with us what their focus areas in AI for the next 12 months will be, with a majority looking to new innovations and vendor solutions (28%), suggesting that we are far from the end of AI developments that suit individual business needs and deliver success:

Investing in AI & ROI

Investment in AI technologies continues to surge and shows no signs of slowing down as we enter the second half of 2024 as organisations recognize and understand in more detail its transformative potential.

When considering AI investment opportunities, it’s important that businesses can effectively navigate the intricacies of building ROI within, to win internal investment in order to propel growth strategies. Conversations need to center around identifying the main stumbling blocks they encounter when allocating resources to AI initiatives and devising effective solutions to address any challenges.

Businesses on the whole seem to be taking a pragmatic approach to AI investments, looking at low risk and high value use cases that can be implemented first, where they can prove ROI and build a business case for further implementation.  While the investment in AI technologies, including both generative and predictive AI, continues to grow, businesses must strategically navigate the complexities of assessing ROI and build frameworks from the start to measure the success based on the metrics that are important to the business (this might not just be financial). By focusing on strategic alignment, resource allocation, risk management, and performance metrics, organisations can undoubtedly effectively harness AI to drive growth and innovation.

Quantum Computing

The global quantum computing market is in huge growth, with the industry projected to grow from $412 million in 2022 to $8.6 billion by 2027 (International Data Corp. analysis) – with this in mind, it’s important that organisations start thinking now about potential quantum use cases, so they are prepared when it enters the mainstream:

“A big boom in internet investment was focused on direct to consumer and then digital online deliveries, but now the focus seems to be moving to deep tech. A focus on quantum is a great opportunity for disruption and for organisations to be successful. Now is a really good time to start thinking about how you can actually use quantum and quantum computing technologies, and how they can be applied.”
Paul Ceeley, Director of Technology Strategy, Digital Catapult

The Convergence of AI & IoT

One of the most transformative trends in digital landscape is the convergence or integration between AI and IoT, especially systems where the AI capability is being increasingly embedded into the edge of the systems near the actual use cases. This enables these systems to make decisions or be informed without having continuous connection to the cloud, which in turn delivers a level of automated functions, providing efficiencies, optimisation, a high amount of the adaptability of user needs and other benefits.

This convergence is not only a technological advancement but also a paradigm shift that promises profound benefits across various sectors.

The AI Security Landscape

Whilst there are tremendous benefits from the merge of AI and IoT, this in turn also leads to an increase in the challenges of rural vulnerability, the fragility of assistance, and potential attack surface for players.

Getting insights into how and what apps and websites people are using, what signals are being transferred in real time and putting these analytics alongside customer behaviour will help us to understand where these anomalies are occurring and enable businesses to detect signals well in advance that lead to potential threats.

Opportunities in this space include:

• Dialogue systems (human to machine interactions
• Speed efficiencies with smarter AI devices.
• Digital credit.
• Pushing the intelligence of edge closer to the data source

Generative AI

Chief AI Analyst at Omdia, Eden Zoller, hosted a session at the recent Lonson Summit that focused on the status of the Gen AI market for enterprises, and took a review of companies who are implementing Gen AI and are directly involved in Gen AI strategies.

The survey results showed that a lot of enterprises are embracing generative AI because of its potential to drive revenue, it’s potential to assist with research and new product development, and how on the whole generative AI is meeting, and in some cases exceeding, expectations against key investment drivers.

You can explore these driving factors in the report: Generative AI Enterprise Survey: Early Adopters 2024, Omdia

Governance & Policy

Whether you have created best practices and standards in house or gone external, it’s important to have a strategic approach to the roll out and implementation of AI in any organisation.

Lots of organisation also don’t know if they are compliant with legal frameworks and regulatory requirements when rolling out AI initiatives, so before implementation begins, it’s important to see if there are any existing frameworks in place and if you are or will be operating in a compliant manner.

Effective ways to govern AI within your organisation include:

• Risk Assessment
• Policy and Procedures
• Transparency
• Training and Awareness
• Monitoring and verification
• Response and Enforcement
• Leadership and Oversight

Ethical & Responsible AI

We’re on the cusp of unprecedented advancements in AI innovations, transforming industries and redefining responsibilities, which is a development, and with AI now moving a pace so responsible AI is now mandatory.

How can businesses put something actionable in place to ensure this mandate is followed? Guiding principles such as transparency, fairness, privacy protected consumer protection are crucial to ensure the future is ethical, and equitable for society.

The principles businesses put in place create the foundations for ethical and responsible AI. It’s really important that organisations understand why standards are so important, having quality of standards in place and know how they can be utilised, especially in a diverse regulatory landscape.

Workforce & Talent

The construct of an AI team will be different depending on what industry you operate in, as well as the size and maturity of the organisation. For example, some sectors may require anything from technical resource through to manufacturing, research and product development and testing.

AI can no doubt assist where previous manual task would go to non-technical experts, increasing efficiency and optimisation as a result. But with the huge amount of time and investment needed in AI solutions, they should very much be considered support tools to any role or function. AI overall should not be seen as the responsibility or sole focus of a specific team, but viewed as a cross functional capability that everyone can utilise, learn and take advantage of.

Delve further into the key insights we uncovered at the event around these topics in the latest Digital Transformational Trends 2024 - A New Perspective.