The 2024 AI Summit in London was a vibrant congregation of cutting-edge research, industry innovation, and thought-provoking talks that reflected artificial intelligence’s rapid progress over the past couple of years. For two days, experts from various organisations offered insights into the current state of AI, focusing on themes such as generative AI, sustainability, quantum computing, robotics, data management and responsible AI. Dive into our highlights, especially AI in manufacturing and AI in energy, and discover what these advancements mean for your organisation.
How AI is Transforming Industries
AI in Energy
AI’s role in the energy sector was explored extensively, particularly its potential to enhance efficiency and sustainability. Speakers from AIQ and other organisations discussed how AI can optimise both upstream activities, such as exploration and drilling, and downstream processes, including distribution. Key applications included the optimisation of reservoirs, monitoring well stability, and improving health and safety through advanced CCTV footage analytics.
As the energy industry transitions long-standing systems and processes into the modern age, AI’s potential to facilitate dynamic pricing and peer-to-peer energy trading was highlighted as a transformative prospect.
AI’s potential in smart grid management, energy consumption optimisation, and predictive maintenance was extensively covered. However, the sector faces considerable challenges, particularly in terms of digital readiness and the scalability of AI use cases.
Manufacturing
The integration of AI into manufacturing was a significant highlight at the 2024 AI Summit. Discussions focused on the development of smart, sustainable factories and supply chains. Panellists from BAE Systems and Haver & Boecker OHG, a German manufacturer, emphasised the unique data challenges in manufacturing. Unlike generative AI, which requires vast amounts of data, manufacturing operations often deal with low-volume data and therefore benefit more from simpler AI solutions. These simpler methods not only meet the industry’s data requirements but also offer greater transparency, which is highly valued in manufacturing settings where trust and clarity are paramount.
Future Potential of Generative AI
Generative AI emerged as a pivotal theme at the 2024 AI Summit, with extensive discussions on its future potential.
Future Capabilities
Colin Jarvis, Chief Architect of Open AI, highlighted the growing importance of model customisation for creating domain-specific solutions. He emphasised the rise of multi-modality in generative applications, where models are increasingly capable of handling audio, images, and text simultaneously. This evolution towards more versatile and adaptable AI models is set to revolutionise various sectors by providing more tailored and effective solutions.
Scaling Generative AI
The summit also delved into the challenges and strategies for scaling generative AI within organisations. Fernando Lucini, Global Lead for Data Science at Accenture, addressed the differences between traditional AI implementations and the newer generative AI systems. Unlike traditional AI, generative AI requires unique frameworks and standards that are still being developed as organisations experiment and learn. A key takeaway from the panel discussion was the necessity of aligning generative AI initiatives with real-world customer problems and implementing them in stages to ensure effective and sustainable integration.
Efficient AI
As generative AI becomes more integrated into business operations, its environmental impact has come under scrutiny. Several speakers, including Paul Dongha from Lloyd’s Banking Group, emphasised the importance of monitoring and mitigating the energy consumption of AI models. The comparison between the energy usage of a single GPT prompt and a Google search underscored the need for more sustainable AI practices. Chae Uhm, Strategy Manager for a South Korean AI chip manufacturer, discussed the market’s growing demand for energy-efficient AI solutions. He highlighted the development of advanced AI infrastructure that balances performance with environmental considerations.
These insights from the summit underscore the transformative potential of generative AI while emphasising the need for careful scaling, real-world application alignment, and a focus on sustainability.
Future Applications of Quantum Technologies
Quantum computing was another focal point of the 2024 AI Summit, with a significant emphasis on its growing potential and future applications. The discussions highlighted the rapid advancements in quantum technology and its implications for various industries. As mentioned earlier, industries like Energy are beginning to explore use cases for quantum computing.
Commercial Viability
A key session featured a panel discussion on the commercial viability of quantum technology, with insights from experts at IBM, Capgemini, and the National Quantum Computing Centre in the UK. While the panellists agreed that quantum computing has not yet reached a scale where it can outperform classical computers across the board, recent advancements in quantum hardware have shown promising results. Adam Hammond, Quantum Enterprise Business Leader for EMEA and APAC at IBM, predicted that in three years, quantum computing might surpass traditional computing capabilities in specific areas.
Quantum Computing in Energy
The potential of quantum computing in various sectors was another topic of discussion. In the energy sector, for instance, E.ON’s Chief Quantum Scientist discussed how quantum computing could revolutionise power plant operations and anomaly detection by handling exponentially complex problems that are currently beyond the reach of classical computing. The ability to optimise operations and predict failures with greater accuracy could lead to significant improvements in efficiency and safety.
These discussions at the summit highlighted the exciting future of quantum computing, emphasising its potential to revolutionise industries through unprecedented computational power. However, realising this potential requires a concerted effort to develop practical applications and drive investment into the quantum sector.
Data Management
Optimising Existing Data
Data strategy was a critical theme at the 2024 AI Summit, with numerous talks emphasising the importance of optimising existing data to enhance organisational efficiency. Leveraging the vast amounts of data that organisations already possess is essential for effective AI deployment.
“Don’t build for what’s available today, build for the capabilities that are coming”
-Colin Jarvis
Speakers highlighted the need for robust data governance frameworks to ensure data quality, consistency, and security across the organisation. By maximising the potential of their existing data assets, companies can drive more informed decision-making and gain a competitive edge.
Breaking Down Silos
A significant challenge in many organisations is the existence of data silos, where information is isolated within different departments or systems. The summit discussions underscored the necessity of breaking down these silos to enable seamless data integration. By creating a unified data infrastructure, organisations can ensure that data flows freely across departments, enhancing collaboration and enabling more comprehensive insights. This approach not only improves operational efficiency but also supports the development of more sophisticated AI models that rely on diverse data sources.
Data Asset Registry
One of the key insights shared at the summit was the value of establishing a data asset registry. This centralised repository of data assets allows all members of an organisation to access and utilise data more effectively. For large manufacturing and trading firms, a data asset registry can provide a fundamental understanding of all business processes, enabling analysts to make strategic decisions based on a holistic view of the organisation’s data. This registry also facilitates better data management and ensures that data is used in compliance with regulatory requirements.
Comprehensive Roadmap
Throughout the two days of the conference, the discussions provided a comprehensive roadmap for organisations looking to harness the full potential of their data assets. Topics ranged from optimising and integrating existing data to ensuring ethical usage and demonstrating value. Establishing a robust data strategy was identified as a crucial component for successful AI adoption. This involves versioning datasets and pipelines, implementing data monetisation strategies, and integrating data governance into the core business strategy.
AI Regulations & Ethical AI
AI Regulations
Regulatory concerns were again a major theme, with discussions on how AI legislation could impact adoption rates and the importance of not over-regulating in a way that hampers innovation.
With speakers from diverse sectors, the consensus was clear: regulation must balance innovation with safety. The recently passed EU AI Act and Colorado AI Safety Law were mentioned throughout several different talks as a new major consideration both for AI creators as well as for AI deployers.
The speakers highlighted that regulation should not stifle innovation but rather encourage responsible development. The dialogue included the need for adaptive regulations that evolve with technological advancements, testing regulatory frameworks in controlled environments before broad application, and addressing unique challenges in high-stakes sectors such as healthcare and energy.
Practical Implementation of AI
Incremental Approach to AI Projects
The summit highlighted the benefits of taking an incremental approach to AI projects. Case studies were presented where teams of analysts used available data to provide tangible benefits through pilot projects and proof-of-value initiatives. This approach allows organisations to demonstrate the value of AI to senior stakeholders, securing buy-in for larger-scale projects. For example, one panel discussed how a new robotics tool, initially developed through a small-scale pilot project, was scaled up to save the firm billions in profit and loss annually.
Overcoming Implementation Challenges
Paul Dongha also provided a comprehensive overview of the hurdles faced during AI implementation. Lloyd’s journey began with establishing an AI forum that included representatives from various parts of the business to create standards for building AI solutions. This forum fostered a culture of learning and knowledge sharing, which was crucial in overcoming obstacles such as skill shortages, data silos, and legacy systems. The forum’s collaborative nature enabled the organisation to address these challenges systematically and effectively.
Conclusion
The AI Summit 2024 was a rich blend of visionary insights, practical applications, and in-depth discussions on the future of AI across various sectors that provided a comprehensive overview of the current state and future directions of AI, underscoring its transformative potential and the importance of responsible innovation.
“AI will not replace humans, but humans using AI will.”
Data strategy emerged as a crucial component for organisations aiming to harness the full potential of AI. The emphasis on optimising existing data, capitalising on its potential, and breaking down silos to improve organisational efficiency was underscored by multiple speakers. Establishing robust data governance frameworks, versioning datasets and pipelines, and integrating data monetisation strategies into the core business strategy were identified as key steps for success. These insights provided a clear roadmap for organisations to enhance their efficiency, drive innovation, and maintain a competitive edge.
The AI Summit 2024 underscored that while AI technology continues to evolve, its successful implementation depends on thoughtful strategy, robust regulation, and ethical considerations. The insights and best practices shared during the summit provide a valuable guide for organisations looking to navigate the complexities of AI adoption and maximise its benefits.
In the words of many speakers, the future of AI is not about replacing humans but empowering them. The mantra, “AI Will Not Replace Humans, but Humans Using AI Will,” encapsulates the summit’s core message: AI is a tool for human augmentation, driving us towards a future where technology and human ingenuity coexist and thrive.
In an increasingly challenging business landscape, the stakes are even higher. Companies that prioritise data governance, invest in robust AI infrastructure, and cultivate a culture of continuous learning and innovation are poised to lead in the 21st century. These organisations will not only optimise their operations and unlock new revenue streams but also set industry standards and outpace competitors. In contrast, corporations that neglect data management and AI integration risk falling behind, as they will be less agile and innovative.
The summit highlighted numerous success stories of companies leveraging AI to solve complex problems and create significant value. From optimising supply chains to enhancing customer experiences and driving sustainability initiatives, the potential applications of AI are vast. Corporations that harness these capabilities will redefine industries, push the boundaries of what’s possible, and lead the charge into a new era of technological advancement.
Ultimately, the AI Summit 2024 showcased that the journey towards AI excellence is one of strategic investment, ethical consideration, and relentless pursuit of innovation. As we look to the future, it is clear that those who embrace AI with a comprehensive and forward-thinking approach will shape the future, setting a new standard for success in the digital age.
Contact Us
At SCSK{digital}, we are dedicated to helping organisations navigate the complexities of AI implementation and achieve success in the digital age. Whether you’re looking to optimise your operations, drive innovation, or ensure compliance with the latest AI regulations, our team of experts is here to support you.
How We Can Help:
- AI Integration: Tailored AI solutions to enhance efficiency and drive innovations across various sectors.
- Compliance Support: Assistance with meeting global standards such as ISO 42001 and the EU AI Act.AI
- Governance: Comprehensive frameworks to ensure responsible and effective AI deployment.
If you have any questions about AI implementation, its impact on your industry, please feel free to reach out to us at digital@scskeu.com. Together, we can build and implement a responsible and effective AI strategy for your business.
Authors:
Chidi Akurunwa – AI Specialist
Simranjeet Riyat – AI Specialist
