Part 2: Expert Predictions For Artificial Intelligence in 2024

In Part 1, experts and startup founders offered many different insights and predictions. More experts have weighed in and made their predictions on the future of artificial intelligence, a tool that has since reshaped the way we live our lives.


Our Experts:


Alastair Brown, Chief Technology Officer, BrightHR
Moreno Carullo, CTO, Nozomi Networks
Steve Harrison, CEO, Anvil Analytical
Tee Ganbold, Co-Founder and CEO, Improvability AI
Tony Hasek, CEO, Goldilock
Aaron McClendon, Head of AI, Aimpoint Digital
Roman Khavronenko, Co-founder, VictoriaMetrics
Rafal Los, Head of Services GTM, ExtraHop
Igor Baikalov, Chief Scientist, Semperis
Pascal Bensoussan, Chief Product Officer, Ivalua
Ed Hill, Senior Vice President EMEA, Bazaarvoice
David DeSanto, Chief Product Officer, GitLab
Qi Pan, Director of Computer Vision Engineering, Snap Inc.


Alastair Brown, Chief Technology Officer, BrightHR



“As the new year approaches, businesses are becoming increasingly reliant on automated time-saving processes. As such, recruitment in 2024 will likely centre around technology that streamlines the often-lengthy journey from listing a job, through to an application being received, right through to onboarding.

Instead of sifting through piles of CVs, a platform where all roles and applicants are listed in a central hub where they can be viewed, managed, and edited, that allows for simple and accurate tracking of applicant’ journeys through the process will be utilised.

Three-quarters of job seekers reportedly lose interest in a role if the recruitment process takes too long, so tools like this will become valuable, especially as 91% companies are facing challenges in hiring.

With the more tedious and time-consuming aspects of the hiring process streamlined, this will free up recruiters and business owners to focus on building relationships with candidates and making more strategic hiring decisions.

As technology continues to advance, we can expect to see new tools and strategies emerge that will help companies find and hire the best candidates for their needs.”


Moreno Carullo, CTO, Nozomi Networks



“In 2024, we can expect new players to enter the cybersecurity market, eager for a piece of the large pie. These newcomers will be driven by cutting-edge technological advancements and will find success through their innovative approaches.

A key factor in their strategy will be the rapid adoption of AI in their product lines, which will set them apart from competitors who are slow to innovate and anticipate trends. Experts have predicted widespread AI adoption for some time, however, AI is a broad term that encompasses various applications. In 2023, Generative AI has emerged as a game-changer, with tools like ChatGPT showcasing its potential in both defence and attack vectors. For vendors dealing with threat actors, these advanced tools have made tasks more manageable and efficient.

By 2024, efficiency will be crucial for success. Companies will be focused on delivering better results at a faster pace. Solutions that save time and money will be highly sought after, as they provide significant efficiencies for businesses.”


Steve Harrison, CEO, Anvil Analytical



“Over the next year, I am expecting AI to play an even more integral role in how companies interpret their data, as its capabilities become more widely known. There is a small evolution on ”prompt engineering” while natural language interfaces will improve greatly, we have found that the way you ask your question can significantly influence the quality of result and so we are doing a lot of work on refining the UI to optimise the results.

One of the biggest revolutions in AI is the recent ability to work with natural language, making it more user-friendly than ever before. This has allowed an entirely new user interface to be created, meaning even someone with no technical expertise can use it.

At Anvil, we find that teams can sometimes find it difficult to understand the story the data is telling them, as the data processing steps can be confusing or not easily visible. The ability for them to directly query data themselves is a real game changer that we are keen to utilise. This will allow teams to be more secure in their decision making, as they can verify for themselves that they will be data-driven and well-founded. We are keen to encourage a culture of curiosity and widespread engagement with data, and we expect this mindset to be at the forefront of data analytics going forward.”


Tee Ganbold, Co-Founder and CEO, Improvability AI



“This year, artificial intelligence escaped its confines of sci-fi and academia, entering the mainstream for its creative applications like writing and art generation. But 2024 will be when AI realises its long-held potential to streamline enterprise operations and supercharge productivity beyond what was previously possible. Rather than just optimising isolated tasks, AI will transform end-to-end workflows, freeing up human talent to focus on more meaningful responsibilities. 2024 is shaping up to be the year AI transitions from a content creation tool to an invaluable business asset.

An old critique of AI is that it’s a solution looking for a problem to solve, rather than addressing specific business needs. However, the truth is that companies don’t need to invent new issues to solve – they already have plenty. For example, the available tools for supply chain optimisation and sustainability reporting are currently fragmented, overly costly, unduly complex, just plain inefficient – or all of the above. These products place massive burden on executive teams without providing the contextual, actionable data that companies need to drive real operational improvements. This is exactly where AI can revolutionise an industry: streamlining arduous processes, while allowing businesses to focus on their genuine objectives.”


Tony Hasek, CEO, Goldilock



“AI will do wonderful things in the year ahead. In fact, it already is – helping to diagnose disease,
accelerating research and development in biology, chemistry, pharmacology and engineering and
accomplishing many other minor miracles.

But the fact is that almost every technology we develop can be repurposed for less worthy purposes.
Regulation of AI will be exceedingly difficult – because it is still a technology in its infancy – and
hamstringing it at an early stage can be a definite competitive disadvantage. In addition, any moves
to hamper its development will play into the hands of jurisdictions with fewer qualms about the
downsides of the technology. Striking a balance between harnessing AI’s benefits and mitigating its
risks will be a defining theme of 2024 and beyond.

What is needed is a method of defending against the downsides of AI, while exploiting the upsides.
Doing this successfully comes down to control. The ability to physically disconnect systems to shield
them from attack or remedy attack, and a method of shutting down AI instances should they become
too powerful or corrupted, is perhaps a more reasonable form of security that can provide some
reassurance that AI safety is not left in the technology’s wake as it continues to progress.

The year 2024 will be a pivotal one for AI, as we grapple with the complex interplay between its
transformative potential and the risks associated with its misuse. By emphasising the need for
control, we can create an environment where AI benefits humanity without jeopardising its safety.
Embracing AI’s transformative power while safeguarding against its potential risks will require a
concerted effort from governments, industries, and individuals alike.”


Aaron McClendon, Head of AI, Aimpoint Digital



“The rapid evolution of AI technologies over the past few years has set the stage for a promising future.

One of the most significant trends we anticipate in 2024 is the widespread integration of AI across industries. From healthcare to finance, manufacturing to entertainment (as we have already seen with the rise of deep-fake use amongst celebrities), AI will continue to crop up in and – mostly – prove its worth by optimising processes, improving decision-making, and driving innovation. Businesses that have hesitated to adopt AI will likely face increased pressure to do so, as competitors gain a competitive edge through AI-powered solutions.

Secondly, AI-driven personalisation will reach new heights next year. From content recommendations to product suggestions, AI algorithms will become even more adept at understanding individual preferences and delivering tailored experiences. However, this advancement also raises concerns about privacy and data security, prompting discussions around responsible AI use.

Ethical considerations will take centre stage in AI development next year following the AI summit in the UK this past year and rising concerns from leaders in the space. In 2024, we expect to see more robust ethical guidelines and regulations governing AI deployment. The AI community will be increasingly focused on addressing bias and fairness issues, ensuring transparency, and fostering responsible AI practices to mitigate unintended consequences.

2024 promises to be a year of accelerated advancements in AI, with its integration into various aspects of our lives becoming even more pervasive. However, this growth comes with a responsibility to ensure that AI is developed and deployed ethically, transparently, and responsibly. We believe that a collaborative effort involving researchers, policymakers, and industry leaders is crucial to harness the full potential of AI while addressing the challenges it presents. Only through careful consideration of the ethical implications can we ensure that AI truly benefits humanity in the years to come.”

Roman Khavronenko, Co-founder, VictoriaMetrics



AI will hide more problems than it will solve

“AI powered, low code interfaces, will become popular additions to most data ops platforms next year. The goal will be to reduce increased operations complexity by asking GPT to write queries or control infrastructure. However, for most GPT outputs the user can assess the quality of the text generated. If an AI is used to translate and interpret between the user and the database, neither party can be sure that the answers are correct.

If the industry is serious about simplifying something, AI should be not only an input interface, but output as well. It should be able to tell whether the result of the query is what was intended. Expect a business to have an issue with an AI powered system misinterpreting a critical task in 2024.

Data engineers will teach AI how to do their jobs

AI developers will incorporate tools to quickly fine tune custom models, model maintainers need to have an easy interface for re-training/correcting their models. Companies that intend to use these tools will need a faster feedback loop to acclimatise models to their new jobs.

Rather than large batches of corrections models can be calibrated output by output:

1. User asks question

2. Model responds

3. User marks it as erroneous

4. Model owner receives the report and generates a correct response

5. Model owner feeds the response back to the model as correction step

6. Model improves

This is one path to fine-tune the models that will take over some aspects of data ops management.”

Rafal Los, Head of Services GTM, ExtraHop



“AI will create more new problems than it solves: The rush to “AI everything” will create new issues technologists will be unprepared for in both how information is leaked, public information is re-purposed, and how facts and truth is conveyed and disseminated through society. The promise of AI – to “improve everything” will largely fail and AI will retreat to well through-out use cases where the technology will improve data analysis and operational scale.”


Igor Baikalov, Chief Scientist, Semperis



“LLM’s such as ChatGPT, are hopefully at the peak of their hype cycle. While a significant technological achievement in the evolution of the Human-Machine Interface, it has little to do with “I” in AI. Its rush release to the public seriously damaged the credibility of technology in the eyes of potential customers, making it look like a well-educated monkey with an adjustable creativity level: set it too low, and it’s just a glorified search engine; set it too high, and it starts spewing nonsense.

The solution is to vet the data used for training, but it’s extremely hard considering the volume and breadth of topics. Crowdsourcing the process runs into the MS chatbot problem – now one has to vet the moderators.

Despite all these problems, LLM’s can be successfully utilised in niche applications, where they are trained on carefully curated data limited to a specific area, such as cybersecurity. It’s still a Large LM which needs a large amount of data to cover the topic in depth, therefore products from the tech giants – like MS Security Copilot or Google PaLM2 – are likely to lead the way and provide pre-trained models for smaller developers to customise and incorporate into their applications.

But LLMs are perhaps best used at the human-machine interface, with the real work being done using structured analytical models tuned to the customer’s environment.”


Pascal Bensoussan, Chief Product Officer, Ivalua



In 2024, Generative AI’s success will hinge on the procurement professionals behind it

“In 2024, AI hype will reach its peak. This time the hype will be matched by meaningful, relevant capabilities, and a raft of generative AI procurement tools will come to market, becoming accessible for procurement professionals. But, against sky-high expectations, procurement leaders must accept that Gen AI solutions are like any other tool – they are only as good as the person using them or the data that it is fed. Leaders will reap the benefits while laggards will be disappointed as they fail to adjust how they work to leverage the capabilities of this innovative technology.

“To reap the productivity benefits from Gen AI, employees must use their knowledge and experience to apply them correctly. Organisations should adopt flexible and extensible AI solutions that can quickly grow to adapt to new use cases which allow users to control the prompts and address the challenges that matter most to their procurement team. Often, getting large language models to accomplish a task reliably, with consistency and precision, requires several iterations in the development and testing of a robust prompt with proper settings, examples, and instructions.

“For example, with a robust configuration, Gen AI could be used in SRM to analyse supplier documents like ESG disclosures and contracts, generating queries and recommended resolutions to issues spotted via performance evaluations. This will help firms to identify potential performance challenges and take concrete action without having to scour hundreds of pages of content manually or create collaborative improvement plans by hand.”


David DeSanto, Chief Product Officer, GitLab



Bracing for the Rise in AI Bias Before We See Better Days

“In the short term, the rapid development and adoption of AI tools and products leveraging AI services will lead to an increase in biased outputs. As most AI services scrape the internet to build training data, the inherent biases of the Internet will propagate into these offerings until needed controls can be added. However, this will serve as a catalyst for the industry to establish rigid ethical guidelines and training interventions, ultimately enhancing the ability of AI tools to be more discerning and impartial. But it’s going to get worse before it gets better.

AI Will Dominate Code Testing Workflows in 2024

The evolution of AI in DevSecOps will transform code testing over the next couple of years. Currently, 50% of all testing is conducted with the help of AI. Expect this to reach 80% by the end of 2024, approaching 100% automation within two years. As organisations integrate these AI tools into their workflows, they will grapple with the challenges of aligning their current processes with the efficiency and scalability offered by AI. This shift promises a radical increase in productivity and accuracy — but it also demands significant adjustments to traditional testing roles and practices.

Code Red: AI’s Escalating Threat to IP and Privacy in Software Security

As AI-powered code creation becomes increasingly adopted by organisations within their software development practices, the risk of significant AI-introduced vulnerabilities and intellectual property loss emerging in the next year is high. The situation will only worsen unless privacy and intellectual property (IP) protections are prioritized around how AI-powered code creation is adopted and deployed. The industry stands at a critical juncture: Without a concerted effort to integrate robust privacy measures, IP leakage will persist and intensify, leading to potentially widespread repercussions for software security, corporate confidentiality, and customer data protection.

From Luxury to Standard: Businesses Will Embrace AI Across the Board in 2024

Integrating AI into products and services will become a standard, not a luxury. With organisations pushing the boundaries of efficiency through AI adoption, 2024 will be the year that more than two-thirds of businesses will embed AI capabilities within their offerings. This shift signifies a pivotal transformation, with companies evolving from mere users of AI to becoming AI-centric in how they deliver their solutions to their users, both internal stakeholders and customers. This trend is not just about staying competitive; it’s about survival, as AI becomes the engine driving innovation and customer value across all market sectors.”


Ed Hill, Senior Vice President EMEA, Bazaarvoice



“AI has the potential to be a game changer for UK brands and retailers, earning the trust of a solid 53% of consumers. In the coming year, it’s set to make waves in British retail, opening doors to streamline operations, jazz up content creation, and amp up the overall customer experience. Yet, finding that sweet spot between human creativity and AI efficiency is key. It’s not just about incorporating AI; it’s about doing it responsibly and ethically, ensuring it complements rather than replaces human input and creativity. This intentional strategy keeps things in line with brand values but also builds consumer trust while helping to dodge any unintended ethical issues.

However, a looming challenge in UK retail is the surge in AI-generated fake ratings and reviews, bringing the risk of everything from misinformation to downright deception. Keeping user-generated content (UGC) genuine and authentic is a must not only in the year ahead but also indefinitely. Brands need to get that the true value of UGC isn’t just about quantity but its authenticity, putting the spotlight on genuine customer experiences to solidify trust. Navigating the evolving AI landscape in UK retail demands a smart, forward-thinking approach—responsible AI practices, transparency, and an unwavering commitment to authentic customer connections are the recipe for success.”


Qi Pan, Director of Computer Vision Engineering, Snap Inc.



“Generative AI will enable AR to understand so much more about the world around us.

That’s because advances in Generative AI learning have enabled us to create training data to train ML models used for AR in new ways, and ultimately, train AR much faster. When we build AR experiences, it’s important for this technology to be able to understand and map the different objects and scenes around us, so we can add an exciting digital layer that elevates our experiences.

Having the ability to achieve this more quickly and in greater detail will allow us to create even more immersive experiences that will create value for people and businesses. This year, we’ve seen AR creators and developers use our AR platform in all kinds of new ways, including to transform the way we experience art, fashion and travel. It’s unlocked greater creativity and, therefore, new experiences for Snapchatters. In 2024, we expect to see even bigger and better AR experiences created across the world. For example, this year we used AI and ML to create an incredibly realistic Barbie Try-On lens to coincide with the blockbuster film release. It went on to be our best performing body lens ever!”