AI Predictions for 2024 from AI in Business
AI Predictions for 2024 from AI in Business
Trusted data to become a critical asset; ChatGPT will become less relevant; more Chief AI Officers coming; Supreme Court could weigh in on generative AI; advances in healthcare seen
By John P. Desmond, Editor, AI in Business
Readers of AI in Business forwarded their predictions for the impact AI will have in 2024. We are publishing a selection here, followed by predictions from selected sources.
Gerardo Fernandez, MD, Cofounder and chief scientific Officer, PreciseDx, innovator in oncology diagnostics:
“Cutting-edge technologies like AI, machine learning, and data analytics are set to revolutionize precision diagnostics, treatment personalization, and overall patient care. These advancements hold the promise of more accurate diagnoses, predictive analytics for diseases, and tailored treatments, ultimately improving patient outcomes.
“However, the path from technological breakthroughs to their incorporation into mainstream healthcare practices faces hurdles. Regulatory processes for test approvals and the necessary adjustments in healthcare systems to accommodate these new technologies take time. The cautious approach to ensuring safety, efficacy, and ethical considerations may contribute to a lag between technological advancement and its widespread adoption in healthcare.
“However, the shift towards digital pathology presents a promising avenue to mitigate the shortage of pathologists and its respective consequences. These technologies streamline workflows and allow offsite work, helping pathologists to analyze samples faster than humanly possible with greater accuracy and efficiency.”
Ivan Lee, CEO and founder of Datasaur, offering an NLP data-labeling platform:
"We'll see a transformative era in the ChatGPT and LLM landscape heading into 2024 as a staggering 90 percent of English speakers will, knowingly or otherwise, integrate LLMs into their daily routines; whether through email, online searches, or engaging with personal assistants like Siri or Alexa. Furthermore, organizations in countries around the world will develop foundation models like OpenAI’s GPT-4 and Llama 2 in many other languages to level the playing field, ensuring a more inclusive and accessible global deployment of these technologies.
“LLMs are predicted to diverge, not converge. For example, the entire finance industry won't use a single finance model. Instead, individual companies will develop proprietary models to meet specific needs. Using a full-sized model like OpenAI's GPT-4 to classify text is like using a MacBook Pro as a calculator. Instead, organizations will build and utilize numerous smaller, lighter weight models that can accomplish tasks more efficiently and at lower cost."
Satyen Sangani, CEO and cofounder, Alation, offering a data intelligence software platform:
“Trusted data will become the most critical asset in the world. In a world that’s inching closer and closer to artificial general intelligence (AGI), knowing what to trust and who to trust will be critical to everything we learn and everything we think we know.
“Highlighting this shift, Forrester predicts that domain-specific, Large Language Model (LLM)-infused digital coworkers will soon assist 1 in 10 operational tasks. This trend has led organizations to focus more on finding, understanding, and governing high-quality, dependable data, which is vital for training AI models tailored to specific business requirements.
“As a result, AI governance is going to gain importance quickly. It involves more than just managing data; it’s about understanding the entire lifecycle of information and models. The analogy of data as the new oil now seems insufficient in the era of generative AI and the challenges hallucinations bring. Merely amassing and analyzing large data sets is no longer adequate in today’s business environment.
“To future-proof AI deployments, organizations will increasingly look to build out a role at the C-suite level to oversee both AI innovation and compliance. AI will lead to the creation of a new generation of chief data officers, existing data leaders who have developed new skill sets. We are about to see the start of a fresh generation of chief data and AI officers focused on ensuring that data foundations of AI models are compliant with new legislation and of a high enough quality to gain the business a competitive advantage.”
Jeff Catlin, EVP of AI Products at InMoment, offering customer experience integration
“ChatGPT will become less and less relevant as the year progresses. Local LLMs such as Llama2 (and whatever comes next) will become the engine of corporate AI. The change is being driven for two primary reasons: data security and the ability to influence the results by augmenting a local LLM with industry-specific content.
“Technologies such as LangChain, which allow users to feed the results of one LLM into another LLM, will become much more important for corporate users than the next, all-knowing LLM.
“Powerful NLP that can tear apart unstructured and semi-structured content by speakers, regions, or problem areas will bring the diagnostic abilities of LLMs to the next level.”
Mass General Brigham surveyed their own experts about what scientific breakthroughs they anticipate having an impact in 2024. Among the responses:
Omar Arnaout, MD, Neurosurgeon, Department of Neurosurgery, Brigham and Women’s Hospital:
“In 2024, machine learning and artificial intelligence (AI) will drive significant advancements in neurosurgery and medicine. These technologies will enable the creation of personalized treatment plans by analyzing patient data, improving surgical precision and enhancing post-operative monitoring.
“AI-powered diagnostic tools will assist neurosurgeons in early disease detection and accurate characterization. Additionally, AI-driven data analysis in neuroscience research will uncover valuable insights, potentially leading to breakthroughs in understanding and treating neurological disorders. Overall, AI will continue to revolutionize neurosurgery, offering more effective, personalized care and advancing our knowledge of the brain.”
Danielle Bitterman, MD, Assistant Professor, Department of Radiation Oncology, Brigham and Women’s Hospital; faculty member, AI in Medicine Program, Mass General Brigham:
“We will see a breakthrough that will allow us to efficiently update and edit generative AI models, such as large language models, so that they are safe, effective and current with clinical knowledge. This will be a major leap toward transformative clinical-AI integration because we will have more control to ensure high-quality output that adapts to new standards of care. Reliable models, refined for expert-level decision-support and education, will be key for clinical translation.”
On his blog,Clement Delangue, cofounder and CEO, Hugging Face, offering a shared machine learning platform, predicted that in 2024:
- "A hyped AI company will go bankrupt or get acquired for a ridiculously low price;
Open-source LLMs will reach the level of the best closed-source LLMs;
Big breakthroughs in AI for video, time-series, biology and chemistry;
We will talk much more about the cost (monetary and environmental) of AI;
A popular media will be mostly AI-generated;
10 millions AI builders on Hugging Face leading to no increase of unemployment."
“That all seems like the direction things are going in,” Delangue commented.
Bernard Marr, author, speaker and consultant, issued his top AI Trends for 2024 predictions via LinkedIn. Here is a selection:
AI Legislation: “AI's unprecedented trajectory isn't solely a fascination for tech enthusiasts—it's now commandeering significant attention from global policymakers. As 2024 beckons, leading nations, including China, the EU, the US and India, are diligently sculpting comprehensive AI policies. Their objectives are three-pronged: to catalyze technological breakthroughs, magnetize global investments, and concurrently safeguard their populace from any inadvertent AI repercussions. Conversations within the industry hint at potential international synergies, suggesting that global collaboration on AI benchmarks and norms could soon materialize.”
Ethical AI: 3. “The expanding footprint of AI in our lives introduces a myriad of ethical dilemmas. As AI mechanisms increasingly inform decisions, spanning from health evaluations to financial counsel, it's imperative that they function with utmost transparency and fairness. However, the challenge extends beyond just engineering unbiased algorithms. We must cultivate rigorous standards to ensure both these systems and their architects remain answerable for their actions. As we approach 2024, experts foresee a blossoming interest in AI ethics education and a heightened prioritization of ethical considerations within AI research and development realms.”
A selection of the Top 10 AI Predictions for 2024 from Forbes magazine:
Nvidia will ramp up its efforts to become a cloud provider. Most organizations access Nvidia’s GPU chips via cloud providers such as Amazon Web Services, Microsoft Azure and Google Cloud Platform. “But Amazon, Microsoft and Google—Nvidia’s biggest customers—are fast becoming its competitors,” according to the account. These cloud providers are all investing to develop their own AI chips as well.
Nvidia rolled out its own DGX Cloud service earlier in 2023. “We predict that Nvidia will meaningfully ramp up this strategy next year,” the authors stated.
A number of Fortune 500 companies will create a new C-suite position: Chief AI Officer. With AI at the top of the priority list for Fortune 500 companies this year, boards are trying to figure out what the powerful new technology means for their business. The Chief AI Officer can spearhead AI initiatives and give the technology a face in the boardroom.
President Joe Biden’s recent executive order on AI requires every federal agency to appoint a Chief AI Officer, meaning that over 400 such positions will be hired across the US government in coming months. (See Executive Order on AI Seen as Model for AI Accountability, AI in Business, December 8, 2023.) The federal government’s actions around AI governance are seen by many as a model for industry, especially in anticipation of coming regulations around AI.
The Microsoft/OpenAI relationship will begin to fray. Microsoft invested over $10 billion in OpenAI, whose models now power many Microsoft products, including Bing, GitHub Copilot and Office 365 Copilot. “The alliance has so far worked well for both groups, but it is a marriage of convenience. The two organizations are far from perfectly aligned,” the Forbes authors stated. “Next year, we predict that cracks will begin to appear in the partnership between these two giants. Indeed, hints of future friction have already begun to surface.”
Additionally, “Given their differing cultures, values and histories, it seems inevitable that the two organizations will diverge in their philosophies and approaches to these issues.”
At least one U.S. court will rule that generative AI models trained on the internet represent a violation of copyright. The issue will begin working its way up to the US Supreme Court, Forbes predicts, calling it a “significant and underappreciated legal risk” looming over generative AI today.
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