Big changes are coming in 2024, with artificial intelligence set to play an even more prominent role in our lives. Here we explore our top AI predictions plus some of the tangible steps you can take to become an AI-empowered business<\/p>\n
t may be the topic du jour, but AI is much more than a flash in the pan. In 2024, the evolution of artificially-intelligent software will continue to rock the boat \u2013\u202ffor organisations, governments, and the public alike.<\/p>\n
So, what\u2019s coming down the line? How will the technology evolve over the next 12 months? And what might this mean for businesses that need to work with and alongside AI?<\/p>\n
We\u2019ve identified five AI predictions for 2024 \u2013 plus the steps your organisation can take to raise the bar with artificial intelligence.<\/p>\n
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At the core of the EU\u2019s fledgling\u00a0AI Act<\/a>\u00a0are a set of rules and processes designed to stop more sinister uses of the technology \u2013\u202flike biometric categorisation systems, behavioural manipulation, and social scoring.<\/p>\n The Act requires any business using AI to self-declare the risk levels of those systems,\u202fwith fines for those who misrepresent their products.<\/p>\n There\u2019s no regulatory body for this, so businesses must get to grips with\u00a0AI regulation<\/a>\u00a0quickly. And start codifying what\u00a0responsible AI<\/a>\u00a0means for their organisation.<\/p>\n Of course, the timetable for compliance will be staggered. Some organisations will be expected to comply sooner than others based on categories and risk levels laid out in the draft Act.<\/p>\n \u2018The incoming AI Act brings much needed guidance, but businesses must move quickly to codify what responsible AI means for their organisation\u2019.\u00a0<\/strong><\/em><\/p>\n The Act\u2019s impact on business innovation will also vary widely from one industry to the next. For highly regulated sectors like medtech, where extensive safety measures are already the norm, the AI Act won\u2019t mean a great deal of change. And the likes of embedded systems in medical devices\u00a0will reportedly have much longer to comply<\/a>.<\/p>\n Ultimately, the\u00a0EU AI Act\u00a0<\/a>\u00a0brings much needed guidance around\u00a0responsible AI<\/a>\u00a0development. It provides more clarity on the subject than we’ve ever had before, helping organisations ensure the AI systems they\u2019re using and developing do not have unintended bad consequences.<\/p>\n The regulation should help rather than hinder AI innovation for organisations that adopt\u00a0responsible AI frameworks<\/a>\u00a0and bake transparency and ethical practice into their innovation and AI development processes.<\/p>\n Best practice here will be to fully audit your AI use and put processes in place that adhere to the AI Act at every step of the development and production of AI-based applications.<\/p>\n At Z\u00fchlke, we\u2019ve been helping clients cement\u00a0responsible AI<\/a>\u00a0practices. You can explore how to develop and scale your platforms, products, and processes in a human-centred and responsible way with our four-part\u00a0responsible AI framework<\/a>.<\/p>\n Fire up the latest version of ChatGPT and it\u2019s hard not to marvel at just how far we\u2019ve come with large language models (LLM) in the space of a year. And the fact that these models are publicly available.<\/p>\n But while it seems a bit trite to say \u2018this is just the beginning\u2019, there\u2019s one field where that\u2019s precisely the case: the field of software development.<\/p>\n Generative AI is already getting good at spitting out basic code. But 2024 will be the year in which AI truly redefines how software development works. Smarter, more robust LLMs \u2013 built directly into commercial products like Microsoft\u2019s CoPilot \u2013 will reshape the entire software development field. Along with redefining how it\u2019s taught.<\/p>\n<\/div>\n<\/div>\n<\/div>\n Artificial intelligence may write (parts of the) code. But to really improve efficiency and effectiveness, we have to ensure that humans will always be in the loop. That\u2019s why we need to start thinking of AI as the tool, rather than the solution. Adobe Photoshop didn\u2019t replace designers, for instance. It just made their work much more powerful.<\/p>\n \u20182024 will be the year in which AI redefines how software development works…The challenge will be finding the optimum combination of humans and machines\u2019.\u00a0<\/strong><\/em><\/p>\n That human part of the equation is going to be key to managing AI use in customer-facing contexts too. Call centres that use solutions based on large language models, for example, will need to find ways to give customers and regulators confidence that those models don\u2019t have bias or inaccuracies. Or, in Chevrolet\u2019s case, that customers don\u2019t\u00a0use AI chatbots to their own ends<\/a>.<\/p>\n Ultimately, this is about finding an optimum combination of humans and machines, with the right safeguards in place to create real benefits for business and society \u2013 while preventing any rogue deployments.<\/p>\n <\/p>\n The misinformation and disinformation space is, unfortunately, only likely to become busier and more complex in 2024. Increasingly, we\u2019ll all need to become vigilant when looking at any piece of media \u2013\u202fwhether it\u2019s text, imagery, or video \u2013\u202fand thinking about its lineage.<\/p>\n \u2018The trend here will be in the ability to differentiate primary and secondary data, with the key question being around verifying the history and point of origin of anything we consume and share\u2019.\u00a0<\/strong><\/em><\/p>\n The 2024 US election race is likely to heat this up,\u00a0for obvious reasons<\/a>. Photos, videos, written articles, and the data that links them will all need to be verified.\u202fIf we can\u2019t ascertain the lineage of this data, then it can\u2019t really be trusted.<\/p>\n This will also have a compound effect on large language models and generative AI. What happens, for example, if the small number of behemoths who own these models train them on faulty, secondary data?<\/p>\n Most organisations don\u2019t have anywhere near the resources needed to own and train language models themselves. So the onus is on those tech giants to train models in the \u2018right\u2019 way, avoid \u2018black box\u2019 systems, and enable citizens and business users to understand the model\u2019s predictions.<\/p>\n For businesses using these models, the best course of action is to adopt a\u00a0responsible AI<\/a>\u00a0framework that facilitates explainable and interpretable AI \u2013 and helps you demonstrate and share data lineage, from source to sea.<\/p>\n With great power comes great responsibility. That\u2019s set to be the battle cry of climate-conscious AI computing solutions in 2024, as the proliferation of useable products brings with it an explosion of computing power requirements.<\/p>\n \u2018This growth will result in a \u2018hockey stick\u2019-shaped leap on energy consumption charts. The raw power consumption that\u2019s required from server farms to power AI solutions will come into sharp relief\u2019.\u00a0<\/strong><\/em><\/p>\n The climate impact of\u00a0cloud computing<\/a>\u00a0is already bubbling up in public interest. But as we see some of 2023\u2019s proof-of-concept products translate into 2024\u2019s operational rollouts, their electricity needs will need to become a more obvious part of corporate ESG responsibility programmes.<\/p>\n Not every AI application or solution will be inherently positive from an environmental standpoint, but AI stewardship and making sustainability a part of your\u00a0responsible AI<\/a>\u00a0framework will enablep you to focus on the environmental impact of AI solutions from the outset.<\/p>\n Best practices include opting for a green cloud provider and aiming for solutions that are resource sensitive, with efficient use of energy and hardware.<\/p>\n These are decisions that should be thought about upfront and on an ongoing basis, rather than as an afterthought.<\/p>\n Gen-AI-empowered business was very much in an experimental phase in 2023, with many organisations experimenting with proof of concepts for internal and external\u00a0ChatGPT use cases<\/a>.<\/p>\n \u2018This experimental phase will continue into 2024, with many businesses unable to deploy generative AI at scale\u2019.\u00a0<\/strong><\/em><\/p>\n In the next 12 months, some organisations will struggle to turn their AI prototypes into reliable, secure, scalable, and human-centric solutions that deliver ongoing value. And they might need to reset their AI aspirations when it comes to implementation.<\/p>\n Why? Because some companies still lack the robust data foundation that\u2019s needed to reap the rewards of AI \u2013 from defining a holistic and human-centred AI strategy, to implementing the right\u00a0data platform<\/a>, capabilities, culture, safety controls, and more.<\/p>\n Many organisations lack or will struggle to define the processes required to productise or \u2018operationalise\u2019 AI. For others, AI-empowered business is still a distant aspiration.<\/p>\n The hard truth is that, if you\u2019re still struggling to convert your data into business value, you\u2019ll struggle to reap the rewards of AI.<\/p>\n <\/p>\n So, these are our AI predictions for 2024 \u2013 and the challenges and opportunities we foresee. But how can your organisation prepare for these changes?<\/p>\n \u2018In a nutshell, our advice is to prioritise transparency at a process level and focus on getting the data \u2018basics\u2019 right. From trust and access, to adopting a responsible AI framework\u2019.\u00a0<\/strong><\/em><\/p>\n In 2024, being open and crystal clear about the source and use of data is a business imperative. It\u2019s becoming critical for helping people understand how technology works. And how, at every level, it\u2019s been made in a human-centred, principled, and responsible way.<\/p>\n For your business, this could mean working directly with lobbyists and regulatory bodies, sharing data openly to navigate antiquated antitrust or anti-privacy concerns, and being prepared to explain your processes at every step.<\/p>\n That level of data transparency will increasingly become a legal requirement. It also makes competitive business sense in a world where trust fosters adoption.<\/p>\n But having proper data with clear lineage is not the only imperative. To maximise value and accelerate innovation, you need to develop AI based on a robust\u00a0responsible AI<\/a>\u00a0foundation. And accelerate your journey towards becoming a data-empowered organisation.<\/p>\n Originally posted here<\/a><\/p>\n2. Generative AI rewrites the rulebook on software development<\/h3>\n
3. Data lineage holds AI content to account<\/h3>\n
4. Green computing steps into the limelight<\/h3>\n
5. Businesses clarify their AI aspirations and strategies<\/h3>\n
How to meet 2024\u2019s AI opportunities<\/h2>\n
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