Part 1: Expert Predictions For Artificial Intelligence in 2024

Artificial Intelligence has come a long way over the past few years. 2023 has been a monumental year for this development, and that means that 2024 has a lot more in store. We will see even more developments and even better uses of AI in our everyday worlds. We’ve asked a few experts what they believe will come about with artificial intelligence in the coming year.
 

Our Experts:

 
David Harrison, UK Technology Strategy & Transformation Practice Lead, KPMG UK
Russell Gammon, Chief Solutions Officer, Tax Systems
Tom Fowler, CTO, CloudSmiths
Sharon Mandell, CIO, Juniper Networks
Giordano Albertazzi, CEO, Vertiv
Thomas Richards, Principal Security Consultant, Synopsys Software Integrity Group
Farley Thomas, Co-founder and CEO, Manageable
Andy Patel, Senior Researcher, WithSecure
Piers Williams, Insurance Lead, AutoRek
Robert Houghton, Founder and CTO, Insightful Technology
Professor Lars Erik Holmquist, Nottingham Trent University
Ian Liddicoat, Chief Technology Officer and Head of Data Science, Adludio
Kinda Savarino, Senior Designer, Billion Dollar Boy
Steve Jordan, Co-Founder, hyperTunnel
Oliver Lemon, Academic Co-Lead, National Robotarium and Professor of Computer Science, Heriot-Watt University, Edinburgh

 

David Harrison, UK Technology Strategy & Transformation Practice Lead, KPMG UK

 

 

“2023 has undeniably been the year of generative AI. But unlike some hot technology trends, GenAI won’t lose its appeal, and I expect it to stay at the top of businesses’ agendas throughout 2024. In fact, the 2023 KPMG CEO Outlook survey revealed that business leaders are continuing to invest heavily in generative AI in search of a competitive edge for the future, listing the technology as a top investment priority in the medium term.

Nevertheless, I do expect regulation and ethical challenges to slow progress. In the same piece of research, 63% of UK CEOs said that the current lack of regulations and direction for generative AI within their industry will be a barrier to their organisation’s success. As a workaround, more businesses will find ways to use it more securely; for example, it will be common for organisations to develop their own Large Language Models for internal use.”

 

Russell Gammon, Chief Solutions Officer, Tax Systems

 

 

“Most people currently aren’t using generative AI in their work, but in another 12 months, you’ll find that it is a far bigger part of daily life.

This will, however, not be to the extent that Elon Musk claims. Will AI take away all jobs? No, I don’t believe so. People don’t want to buy from or interact with soulless robots, they want the human touch, so all industries will continue to need people. Implementing generative AI is about automating processes to enhance human roles, not removing them. In finance and accounting, this means that professionals no longer have to collect and analyse the data points, they can simply review the outcomes and apply their tax knowledge to the data set. By taking over mundane admin tasks, junior team members can take on higher value roles straight out of university – roles that they have studied and trained to do.

“It is important to remember that it is also not a one-size-fits-all approach – accessibility, bias and inaccuracy issues must continue to be addressed. Generative AI is in its infancy and still requires a lot of training. Whilst it is impressive and revolutionary, we must still proceed with caution. But in 2024 we will continue to see AI as a helping hand, or co-worker, rather than a replacement.”

 

Sharon Mandell, CIO, Juniper Networks

 

 

“In 2024, a primary focus will be how we operationalize GenAI, even if we haven’t figured out the challenge of cost management. As we move beyond proof-of-concept (POC) phases, the productivity gains and potential savings will become increasingly clear, especially in areas such as coding, test creation, legal, and marketing content creation or validation. The pressure will also be on IT to translate these gains into real benefits or cost reductions. Additionally, the push for GenAI adoption will continue to uplift the well-established AI solutions that have been in use before the advent of GenAI.

We’re also anticipating that security challenges will continue to evolve and require more focus and investment. This includes securing GenAI systems themselves. We expect that a growing percentage of our IT budget will be spent on prevention, mitigation, and recovery efforts in response to evolving threats. Additionally, the need to ensure compliance with new regulatory requirements, particularly in the United States and other regions, will be a big focus.”

 

Tom Fowler, CTO, CloudSmiths

 

 

“AI adoption has created a massive amount of excitement and hype, but real-world, use cases are only now starting to come to the fore. So, we will still come down the hype curve somewhat and find out where the actual, useful AI use cases are (specifically in the Gen AI space). However, we are seeing a massive uptick in demand for fine-tuning foundational models and hosting them, so an increase in the demand for GPUs and storage is also on the up-tick. GPU prices are still high, but I expect that as demand and supply even out over the coming months and years, this should start to become affordable even for mid-size firms.

Gen AI will definitely continue to mature, and we will see a consolidation of tooling and frameworks with dominant players emerging that allow the deployment, training and consumption of domain-specific LLMs to become simple and commonplace. Fine-tuning models will become the realm of the business analysts, collecting and preparing data, rather than purely the data scientist.”

 

Giordano Albertazzi, CEO, Vertiv

 

 

Intense, urgent demand for artificial intelligence (AI) capabilities – and the duelling pressure to reduce energy consumption, costs and greenhouse gas emissions – loom large over the data centre industry heading into 2024. The proliferation of AI (as Vertiv predicted two years ago) along with the infrastructure and sustainability challenges inherent in AI-capable computing will be felt across the industry and throughout 2024. Finding ways to help customers both support the demand for AI and reduce energy consumption and greenhouse gas emissions is a significant challenge requiring new collaborations between data centres, chip and server manufacturers, and infrastructure providers.

Surging demand for artificial intelligence across applications is pressuring organisations to make significant changes to their operations. Legacy facilities are ill-equipped to support widespread implementation of the high-density computing required for AI, with many lacking the required infrastructure for liquid cooling.

In the coming year, more and more organisations are going to realise half-measures are insufficient and opt instead for new construction – increasingly featuring prefabricated modular solutions that shorten deployment timelines – or large-scale retrofits that fundamentally alter their power and cooling infrastructure. Such significant changes present opportunities to implement more eco-friendly technologies and practices, including liquid cooling for AI servers, applied in concert with air cooled thermal management to support the entire data centre space.
 

 

Thomas Richards, Principal Security Consultant, Synopsys Software Integrity Group

 

 

“With the ever-expanding availability of AI/ML LLMs, companies are under pressure to use the technology for both internal and external tools and products. Both of these scenarios will introduce new risks to an organization that didn’t exist 6 months ago – and there’s little guidance on how to deploy these systems securely. Based on trends we have seen with early adoption of mobile and cloud technologies; I expect there to be some major breaches and compromises during the infancy of this technology. AI/ML model data poisoning and secret extraction will continue to rise in popularity as attack paths against these systems. A whole new class of attacks are now possible against this techno-social domain where humans can find ways to manipulate, or social engineer, a computer into performing actions it is programmed not to. I expect this space to expand quickly as organizations will face these challenges and new tooling is made available to both assess and provide safeguards around how the technology is used.”

Farley Thomas, Co-founder and CEO, Manageable

 

 

“There is no doubt that as we go into 2024, AI will continue to have a dramatic effect on the way we work. But, AI isn’t the first thing to cause disruption to the workforce; over the last 10,000 years, we’ve had huge shifts in the nature of work and the skills we needed from industrialisation, to the Web and so on. So, when entering the new year, we should be talking about reskilling and upskilling rather than how AI might bring about the demise of work.

Wharton’s Professor Lynn Wu confirms in her research that workers will not necessarily be displaced by automation and AI. Instead, as the nature of the work shifts, it demands different skills and this is going to impact the managerial level in particular. If all you’re doing is supervising processes and production, this work is likely to be perfect for AI to do better and cheaper. However, the need for high-value work is only going to increase, especially when building the right team dynamic, shaping culture, motivating people and helping them grow. This is the human touch that will coexist with AI and, in this sense, I like the idea of seeing AI as a co-pilot for complex human work, such as leadership. As such, I expect we’ll see a phasing in of AI to support leaders with complex decisions and tasks.”

 

Andy Patel, Senior Researcher, WithSecure

 

 

“AI will be used to create disinformation and influence operations in the runup to the high-profile elections of 2024. This will include synthetic written, spoken, and potentially even image or video content. Disinformation is going to be incredibly effective now that social networks have scaled back or completely removed their moderation and verification efforts. Social media will become even more of a cesspool of AI and human-created garbage.

The cybercriminal ecosystem has become compartmentalised into a multitude of service offerings such as access brokers, malware writers, spam campaign services, and so on. On the disinformation front, there are many companies that pose as PR or marketing outfits, but who provide disinformation and influence operations as services. Where relevant, cyber criminals and other bad actors will turn to AI for the sake of efficiency. They will use generative models to create phishing content, social media content, deepfakes, and synthetic images and video. The creation of such content requires expertise in prompt engineering – knowing which inputs generate the most convincing outputs. Will prompt engineering become a service offering? Perhaps.”

 

Piers Williams, Insurance Lead, AutoRek

 

 

AI will not solve all the insurance industry’s problems in 2024

“Innovations in fintech have driven the pace of change in the financial services industry, transforming the way much of the sector conducts its back and middle-office operations. However, the insurance industry still lags behind. 2024 will see the insurance sector playing catch-up, focusing on how automation – rather than AI – can create efficiency, improve controls and ensure operational resiliency.

“Back-office operations are the key source of inefficiencies for insurers, with many firms turning their attention to AI and advanced analytics to streamline processes. While there is a lot of hype in the corporate world regarding AI’s potential, it is likely still several years until we see tangible solutions leveraging AI to support back and middle office finance operations processes. Insurers should currently be prioritising investment in intelligent automation over AI.

“AI is not a magic wand that will solve all problems. Much like a human, AI will make mistakes and we will likely see a new concept of ‘AI error’ over the coming years as it is used more and more. Due to its ability to supplement information, and learn from the data that feeds it, AI can come to its own conclusions, which when viewed in the context of a financial control processes is not needed. Financial control processes at their core have a correct and incorrect logical outcome, does data meet certain criteria or not, which is the core validation a reconciliation process is looking to perform. Intelligent automation also typically follows a set of pre-defined rules, rather than attempting to simulate human thoughts or spot patterns. If you adopt AI to make decisions in outcomes where data doesn’t conform, then you introduce the risk of AI error in place of human error.

“Economic headwinds, which are set to continue well into the first half of 2024, also mean that firms need to be optimising resources and increasing efficiencies, which automation has the power to do.”

 

Robert Houghton, Founder and CTO, Insightful Technology

 

 

“AI and automation are the buzzwords of the year, significantly changing our work landscape and set to transform our economy and social norms. Next year, AI as a tool for compliance will be inescapable.

“Take generative AI. It’s a game-changer for financial institutions in streamlining and securing compliance processes. Imagine a trading floor where every call and message is monitored. Certain phrases or words will trigger an automated alert to the compliance team.

These alerts are typically sorted into three tiers of concern. A low-level alert might be triggered by a trader swearing in a conversation. These are common occurrences that result in hundreds of daily alerts, usually reviewed manually by offshore companies. This traditional review process is time consuming, open to mistakes and inconsistent.

“Enter generative AI, with its dual capabilities. Firstly, it can spot the misdemeanour in real-time. Secondly, it can understand the context to see what risk it poses. If someone swore, perhaps because they were quoting a strongly worded news story, it’s not a risk. Generative AI can tell the difference between that and someone using bad language in anger, thereby reducing false positives.

“In the coming year, financial institutions will look at how these AI and automated decision-making processes can be explained, recorded and saved. However, it can’t be a “black box” that holds the fate of a trader within. By creating an audit-friendly trail, businesses will improve their chances of avoiding regulator penalties.”

 

Professor Lars Erik Holmquist, Nottingham Trent University

 

 

“The keys to understanding the next year of AI innovations are specialisation and convergence of data. At this point, the power of the underlying AI models developed by major companies are more or less equivalent. What differentiates their capabilities is the data they have access to, and even that edge is disappearing as OpenAI, Google, Amazon, Meta and the rest gobble up more and more of the text and images that are already available on the internet.

Instead, we will see a rise in services that apply AI to very specialised data. Start-ups are already offering services where they take specific client information, say internal sales figures or in-house produced media, and apply AI to provide deeper analysis or generate new content. This will lead to “AI in a box” solutions of tailor-made models for different purposes and domains.

Simultaneously, we will also see the merging of diverse types of data. Major companies already access their users’ private emails, listening habits, exact location and so on. Combining this user-generated data with massive amounts of existing text and media will enable a new wave of even more personalised services. It will also raise new security and privacy issues as the industry acquires ever more intimate knowledge about their customers.”

 

Kinda Savarino, Senior Designer, Billion Dollar Boy

 

 

“In 2024, AI technology is predicted to transform video capabilities, enabling marketers and creators to explore novel concepts and storytelling techniques.

“This year, AI made a thumb-stopping debut in static imagery, gaining creators thousands of followers and appearing in luxury brand campaigns like Versace and Gucci.

“This success paves the way for AI in moving imagery, going from gimmickry to high-quality, narrative-rich content. These advancements promise to engage audiences more deeply than ever before, showcasing AI-enhanced videos that blend technological innovation with compelling storytelling.”

 

Ian Liddicoat, Chief Technology Officer and Head of Data Science, Adludio

 

 

“In 2024, we can expect the integration of Artificial Intelligence and Machine Learning to steadily increase in digital advertising applications. Most notably, campaign optimisation, creative development, and search.

“Indeed, as AI evolves and the industry continues to align itself with the pace of innovation, there will be major shifts in the advertising landscape. For example, creative agencies will likely diverge into two distinct propositions: those that fully embrace and endorse AI in creative development and production and those that resist this transformative shift. Likewise, programmatic advertising volumes will become more polarised as some brands opt to manage it in-house, while new vendors will launch AI-led, open programmatic platforms that offer a better solution.

“Of course, it won’t just be brands and companies taking advantage of AI. We may begin to see instances in which consumers themselves start to use AI technologies to govern how their profiles are accessed and visualised across a range of platforms. This could see a resurgence in positive ad preferences, where Machine Learning is used to direct ad content to consumers that is more likely to be relevant.”

 

Steve Jordan, Co-Founder, hyperTunnel

 

 

“AI is at the heart of a completely new robot-led construction method that will see its first commercial projects realised in 2024.

Pioneered by British infratech scale-up, hyperTunnel, the wheel is being re-invented in terms of how tunnels and underground structures are built, monitored and maintained.

In the near future, tunnels will be built by thousands of swarming robots, working semi-autonomously via a grid of underground pipes to 3D-print structures into the existing geology. This game-changing construction method is supported by AI, VR, machine learning, simulation and digital twin technologies. It means underground construction projects can be completed faster, safer and with less disruption to the environment. Cities will be able to afford to put more infrastructure underground, bringing significant societal benefits.

AI underpins the performance of the robot swarm. The bots can generate, process and understand a huge magnitude of available data in the face of real-time variables, while learning and responding dynamically to their local conditions and informing the rest of the swarm.

Last October, hyperTunnel revealed the world’s first entirely robot-constructed underground structure, built at its R&D facility in the North Hampshire Downs. The company recently announced its first exclusive distributor agreement with AmcoGiffen for the application of its technologies and systems in the UK rail sector.”

 

 

Oliver Lemon, Academic Co-Lead, National Robotarium and Professor of Computer Science, Heriot-Watt University, Edinburgh

 

 

Oliver is also the Director of the Interaction Lab, which focuses on conversational AI, NLP, machine learning approaches to spoken and multimodal interaction, and Human-Robot Interaction. He is co-founder of Alana AI

“2024 is poised to be a transformative year for artificial intelligence (AI).

In the workplace and on social media, Generative AI, capable of producing creative text and images, will be used in more everyday workflows, for example in drafting emails and other communications. Gen AI can also be used to rapidly create misinformation, fake images, and even fake videos.

Gen AI will also continue to grow to provide the underlying engine for robotics and autonomous systems. Gen AI models will combine robot vision, planning, and navigation with conversational natural language interfaces for robots. In essence, we will see the further evolution of socially aware robots.

AI’s role in drug discovery and development is likely to accelerate, with algorithms capable of identifying potential drug candidates, predicting their efficacy and safety, and optimizing their design. This could lead to faster and more effective treatments for some diseases.

In healthcare, AI will provide information for patients, assist with patient recovery monitoring, and provide AI co-pilots for medical professionals, improving healthcare outcomes and reducing costs.

Finally, the ethical implications and legal governance of AI will become ever more important, with the development of legislation focusing on fairness, transparency, accountability, and AI safety.”