Given the developments in 2023, it’s no surprise that generative AI capabilities and their impact on the world at large are shaping the predictions for the year ahead in technology and the AI space generally.
The launch of ChatGPT on November 30, 2022 ushered in what many are calling a paradigm shift. In response, organizations and countries alike are creating their own AI strategies, regulation is starting to take shape, and companies are still grappling with how and where to integrate it in their business.
Notably, this is all underscored with a sense of urgency that feels unparalleled in recent years. The transformational nature of these capabilities has put AI into conversations everywhere, and the sense of needing to keep up (much less stay ahead), is palpable.
To that end, we have collected some of the predictions for what we can expect next year in the world of AI development and adoption. Here are the dominant themes:
- GenAI for all: Whether you’re an AI pundit or skeptic, knowingly or not, you will be subjected to use of generative AI in 2024. The increased productivity and creative potential offered by generative AI promise significant gains for the enterprise.
- Hold on for a bumpy ride: We are in the gold rush period for generative AI and AI in general; companies are moving fast to adopt, although the use cases and applications are still not always clear or settled.
- Plan for regulations: Managing governance will be challenging but necessary. The European Union’s guidelines will serve as the bellwether regulatory framework; if EU requirements are met, the thinking is that most other requirements will be satisfied.
- Choose wisely: Due to the financial and environmental costs associated with compute power required for LLMs (and chip availability), smaller enterprise and private language models will start to gain traction.
- Spend wisely: Shifts in IT spending will move from the cloud to AI.
Read on for the detailed predictions from other experts in the AI space that can help you prepare for the year ahead.
Generative: The Gateway to AI
According to Deloitte, generative AI features embedded in existing software will be the “gateway to AI” for most enterprises; users probably won’t notice. While pricing models will be mixed, generative AI could create $10 billion in revenue for enterprise software companies by this time next year.
When it comes to regulation, companies will need to balance compliance and innovation, and “existing and drafted European Union regulations are likely to influence generative AI globally.”
The EU model and related fines would apply to anyone operating in or selling into EU countries, and other markets are likely to use this as a template for their own regulation. Not surprisingly, when it comes to personal data, it’s expected that generative AI will need to comply with the tenets of the EU’s General Data Protection Regulation, GDPR, established in 2018. This includes requirements for personal data processing, and the right to modify or erase data, and rules about bias and traceability.
Based on IDC’s forecast that enterprises worldwide would spend nearly $16 billion on generative AI solutions this year, Deloitte predicts that this will increase by 30% in 2024.
Much of this spending will go to cloud service providers, but also to data scientists. That’s because companies will want to avoid the risks and expense of models trained on public data. They will do so by training generative AI on their own data and deploying their own models—which matches with our own prediction earlier this year. To move forward successfully, companies will need to be ready to address hurdles around the necessary skills, expertise, access to GPUs and know how to identify the right use cases.
AI’s Watershed Moment
IDC’s 2024 predictions “are largely centered around the emergence of AI as a major inflection point in the technology industry.”
AI will be core to the business of every IT provider, replacing the cloud as the main driver of innovation. In fact, every industry and application will be impacted by AI, with AI-related initiatives accounting for 40% of core IT budget. To stay competitive, companies will need to invest in more data and skills, which will be crucial for getting value from their AI investments.
From Hype to Intent
According to Forrester, the majority of organizations are experimenting with generative AI in real use cases. The enterprise adoption of generative AI between July and September of 2023 represented “one of the fastest mass adoption rates of a new technology in the enterprise.”
In their 2024 predictions, Forrester says generative AI and AI in general will live up to the massive hype we’ve seen this year and drive real business growth:
- Business, technology and marketing budgets will all include generative AI, which will be used to augment creative problem-solving by up to 50%, and 60% of skeptics will use and value the technology next year.
- Companies will have multiple options to choose from as they build out their AI strategy. Open source will be the choice for 85% of enterprises.
- Generative AI working behind the scenes will be key to augmenting the capabilities of customer service agents, allowing them to resolve problems and answer questions faster and communicate more clearly.
AI Will Bring Fundamental Change
According to PWC’s 2024 AI Business Predictions, not only is generative AI making transformation itself more urgent, it’s also taking transformation to new heights, making it possible to handle previously out of reach processes and skip others altogether.
Even if 73% of US companies are using AI in some area of their business, the key to ROI depends on being able to make the right choices.
Just using generative AI and embedding some capabilities aren’t enough. Companies must prioritize patterns that can scale—for example, using it to extract insight from unstructured text data to help knowledge workers improve decision making.
In 2024, trust in AI will be critical. It’s not just about data security and compliance, but an approach that is based on responsible AI and the data practices and policies that ensure trust is built in, not bolted on.
Generative AI is making it easy to incorporate generative capabilities with no- or low-code scenarios, and this will give birth to a new generation of products and services. Just don’t forget the robust governance!
AI Myths vs. Reality
SAS software asked several of its executives and experts to weigh in on the trends and developments that they believe will be key for 2024, with many centered around AI. They include:
- Generative AI will not replace a comprehensive AI strategy. Generative AI is not a standalone technology, and it will increasingly be seen as something to augment industry-specific AI strategies.
- Generative AI will be critical for both finance and healthcare, where it will be used to combat fraud and improve patient care, respectively.
- Insurers must to proceed with caution when it comes to generative AI. Rather than rushing to roll out autonomous systems, insurers need to move intentionally in order to deploy AI that is fit for their business models and fit for regulatory oversight.
AI Predictions to Keep in Mind
As many have said, it has been a transformative year for AI. In addition to the themes and trends above, the clear imperative is that companies must be ready for AI and the opportunities and challenges that come with it. This readiness includes everything, from your strategic vision, to your data and infrastructure, to your people and policies.
As you look ahead to 2024, keep in mind that:
- Generative AI is the fastest adopted technology in history. Things are moving quickly and mistakes will be made: from overspending to focusing on the wrong use cases to choosing the wrong vendor.
- One of the biggest mistakes is to assume that LLMs and generative AI can or should be used to solve every problem. If the only tool you have is a hammer, everything starts to look like a nail. Remember: generative AI and LLMs are not an entire solution, but a component of a solution. A flexible approach like the Hybrid AI methodology uses multiple AI techniques (Symbolic AI, machine learning, and LLMs) to develop the best solution for the problem you need to solve.
- Regulators are watching, as are journalists and your customers. There will be a greater emphasis on Responsible AI as generative AI becomes more widespread. Make sure the approach you choose includes a human in the loop.
- Finally, implementing an AI strategy is complex. The AI skills shortage will create a ceiling on the pace of enterprise innovation. Choose to work with teams and companies that have experience solving the same types of problems you are trying to address.
