Artificial intelligence (AI) is the simulation of human intelligence processes, especially learning and adaptive behavior, by machines.
AI is presently powering a wide variety of business and consumer applications, such as:
Owing to its potential, AI is one of the most active areas of technological development, particularly in process automation, revolutionizing how we work. In a fast-paced environment where one development, like OpenAI’s ChatGPT, can impact the world literally overnight, many enterprise leaders are understandably curious – even anxious – about current and coming AI trends, hoping to leverage artificial intelligence platforms to improve their productivity, profitability, and competitiveness.
Top Ten AI Trends
Job Security
The debate over the future role of humans in an increasingly AI-dominated business space is not only continuing but intensifying. As revealed in a recent Stanford University report, “Rapid advances in AI threaten to eliminate many jobs, and not just those of writers and actors. Jobs with routine elements, such as in regulatory compliance or clerical work, and those that involve simple data collection, data summary, and writing tasks are likely to disappear.”1
On a more optimistic note, the BBC suggests that “Artificial intelligence is likely to become a powerful tool for workers with disabilities.
“First, many machine-learning tools developed to benefit disabled workers could become increasingly available, believes Victor Santiago Pineda, director of the Inclusive Cities Lab at UC Berkeley. Think, for instance, algorithm-based speech-to-text and text-to-speech tools that provide additional information to visually- and hearing-impaired users, respectively.
“‘AI-powered assistive technologies have the potential to break down barriers and empower individuals with disabilities, fostering a sense of independence and inclusion,’ he says.”2
Cyber Attacks
The UK’s National Cyber Security Centre (NCSC) has concluded that “Artificial intelligence (AI) will almost certainly increase the volume and heighten the impact of cyber attacks over the next two years.”
Separating the cyber bad guys into three classes, the NCSC predicts that:
Highly capable state threat actors will be “best placed to harness AI’s potential in advanced cyber operations against networks, for example, use in advanced malware generation.”
Capable state actors, commercial companies selling to states, organized cyber crime groups will provide the “most capability uplift in reconnaissance, social engineering and exfiltration. Will proliferate AI-enabled tools to novice cyber actors.”
Less-skilled hackers-for-hire, opportunistic cyber criminals, hacktivists will provide a “lower barrier to entry to effective and scalable access operations – increasing volume of successful compromise of devices and accounts.”3
Generative AI
A subset of machine learning, generative AI (GAI) refers to programs that can generate unique business, literary, and artistic content, creating original digital images, video, audio, text, and computer code.
The technology, which quite literally erupted in November 2022 with the release of OpenAI’s ChatGPT program, is trending as follows:
GAI is going mainstream. According to analyst Vincent Koc, who cites a Forbes analysis, “97 percent of business owners already believe that generative AI tools such as ChatGPT will have a positive impact to their business.”4
GAI is turning multi-modal. OpenAI’s GPT-4 model can now respond to audio and visual input.5
GAI is incorporating RAG, or “retrieval-augmented generation” technology. IBM describes RAG as “an AI framework for improving the quality of [Large Language Model (LLM)-generated] responses by grounding the model on external sources of knowledge to supplement the LLM’s internal representation of information.”6 Importantly, RAG is expected to reduce the incidence of GAI “hallucinations.” One of the primary problems with ChatGPT (and other GAI chatbots) is their propensity to make things up, to lie or exaggerate even in situations where a specific fabrication may be obvious. Unfortunately, in many, if not most, cases a GAI deception is not readily discernible, rendering a chatbot’s output unreliable, even harmful depending on its context.
AI Regulations
Given the level of concern about AI – even among its most ardent advocates – there are widespread calls, even demands, for more (and more stringent) AI regulations, with numerous jurisdictions having already implemented AI laws and guidelines. The coming months and years should produce an avalanche of AI legislation, involving issues such as:
- Job security
- Personal privacy
- Intellectual property protection
Small Language Models
Analyst Vincent Koc believes that “2024 might very well be the year of the small foundational models. These specialized, purpose-built AI models are set to take center stage, outshining their generalized counterparts in efficiency and precision.
“Organizations that have either developed their own foundational models or fine-tuned existing ones to their specific use-cases are poised for success. This approach aligns with the 80:20 rule, where the focus is on smaller, tailored models that cater to specific needs rather than attempting to appeal to the masses with generalized solutions.”7
Open Source AI
Given the cost of acquiring and implementing commercial AI systems, many would-be practitioners are considering “open source AI.”
Surveying the short-term opportunities, analyst Lev Craig reminds us that “Early in the year, open source generative models were limited in number, and their performance often lagged behind proprietary options such as ChatGPT. But the landscape broadened significantly over the course of 2023 to include powerful open source contenders such as Meta’s Llama 2 and Mistral AI’s Mixtral models. This could shift the dynamics of the AI landscape in 2024 by providing smaller, less resourced entities with access to sophisticated AI models and tools that were previously out of reach.”8
Shadow AI
Posing an IT governance conundrum, “shadow IT” refers to employees’ unauthorized use of third-party software and services, a practice that makes it difficult, if not impossible, for enterprise officials to exercise control over their IT infrastructure. Now, in the wake of shadow IT comes “shadow AI,” or the unauthorized use of AI applications, like ChatGPT.
As analyst Lev Craig observes, “Shadow AI typically arises when employees need quick solutions to a problem or want to explore new technology faster than official channels allow. This is especially common for easy-to-use AI chatbots, which employees can try out in their web browsers with little difficulty – without going through IT review and approval processes.”9
Artificial General Intelligence
In addition to OpenAI and Google, Meta CEO Mark Zuckerberg has expressed a desire to create an “artificial general intelligence” (AGI) capability. AGI exhibits human-level intelligence and awareness across a full range of cognitive tasks. Although Zuckerberg denies it, his interest in AGI may signal a diminishing involvement with the “metaverse,” a concept he championed – at great risk to his Facebook empire – only two years ago. But as Zuckerberg proclaimed to analyst Alex Heath, “I don’t know how to more unequivocally state that we’re continuing to focus on Reality Labs and the metaverse.”10
Copyright Infringement
Most newspapers, magazines, journals, publishing houses, and individual writers and authors remain united in their opposition to the unrestricted – and uncompensated – access to copyrighted materials by AI firms like OpenAI and Microsoft.
In one of their latest legal actions, on December 27, 2023, The New York Times filed suit against OpenAI and Microsoft for copyright infringement, “contending] that millions of articles published by The Times were used to train automated chatbots that now compete with the news outlet as a source of reliable information.
“In its complaint, The Times said it approached Microsoft and OpenAI in April to raise concerns about the use of its intellectual property and explore ‘an amicable resolution,’ possibly involving a commercial agreement and ‘technological guardrails’ around generative A.I. products. But it said the talks had not produced a resolution.”11
To help preserve a place at the proverbial table should some reasonable proposal be proffered, one can expect other content creators to seek copyright relief in US and international courts.
Help Wanted: AI Expertise
As anticipated, the rapid growth of artificial intelligence, especially in the enterprise space, is exhausting the already thin ranks of AI experts. It’s the same phenomenon affecting CSOs who are seeking people with advanced cybersecurity skills and credentials.
Recommendations
As we witnessed with ChatGPT and recent advances in robotics, artificial intelligence technology is extremely valuable and volatile. As a result, enterprise execs should direct their various research departments to focus on AI developments. A prudent course is to establish an inter-departmental “AI Working Group,” charged with:
- Cataloging new and enhanced AI capabilities;
- Imagining how these capabilities might be applied to enterprises processes, products, and services;
- Monitoring new AI regulations and their impact on enterprise governance, risk and compliance (GRC);
- Conversing with industry partners to identify AI best practices; and
- Working with employees to enable efficient and effective human-AI interactions.
Web Links
Microsoft: https://www.microsoft.com/
OpenAI: https://www.openai.com/
US National Institute of Standards and Technology: https://www.nist.gov/
References
1 Daron Acemoglu and Simon Johnson. “Choosing AI’s Impact on the Future of Work.” Stanford University. October 25, 2023.
2 Leah Carroll. “AI in 2024: Five Trends Workers Need to Know.” BBC. January 5, 2024.
3 “The Near-Term Impact of AI on the Cyber Threat.” National Cyber Security Centre. January 24, 2024.
4 Vincent Koc. “Navigating the AI Landscape of 2024: Trends, Predictions, and Possibilities.” Towards Data Science. January 2, 2024.
5 Lev Craig. “10 Top AI and Machine Learning Trends for 2024.” TechTarget. January 4, 2024.
6 Kim Martineau. “What Is Retrieval-Augmented Generation?” IBM. August 22, 2023.
7 Vincent Koc. “Navigating the AI Landscape of 2024: Trends, Predictions, and Possibilities.” Towards Data Science. January 2, 2024.
8 Lev Craig. “10 Top AI and Machine Learning Trends for 2024.” TechTarget. January 4, 2024.
9 Ibid.
10 Alex Heath. “Mark Zuckerberg’s New Goal Is Creating Artificial General Intelligence.” The Verge | Vox Media, LLC. January 18, 2024.
11 Michael M. Grynbaum and Ryan Mac. “The Times Sues OpenAI and Microsoft Over A.I. Use of Copyrighted Work.” The New York Times. December 27, 2023.