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Mention AI and everyone wants to talk about OpenAI — about Microsoft’s multi-billion dollar investment in it, about GPT 3.5 and GPT 4, Sam Altman’s firing and subsequent reinstatement as CEO and the rumors that the whole kerfuffle may have been about board concerns about new tech developments at the company.
However the generative AI story of the past year was about much more than just one company. It was about all the other companies rapidly developing their own large language models (LLMs) and, in the workplace context, the impact such technology will have on employees and companies.
2024 Will Be a Year of Acceleration and Reflection
Thomson Reuter's chief product officer David Wong believes that the big lesson of 2023 is that generative AI can act as a force multiplier and 2024 will be the year we start to see that impact.
Organizations were quick to test the waters in 2023, he said. Citing Thomson Reuter's recent research, he said that 91% of C-Suite professionals are using it already, or plan to deploy it very soon, with key focus areas being customer satisfaction, operational efficiency and the acceleration of digital transformation.
Furthermore, 45% of professionals have identified their biggest AI aspiration as improving productivity, which survey respondents believe will result in critical advantages for their talent, customers and work environment.
These promises haven't yet translated into reshaping daily work, although the changes will likely start surfacing over the next year. The goal, Wong said, is to use generative AI for mundane tasks that typically takes hours to do so they can now be done in a few seconds.
Wong believes 2024 will be a year of transformation although he cautions hurdles remain, notably issues around ‘hallucinations,’ data accuracy and ethics.
"Recent research found that professionals have ongoing concerns about AI around accuracy, data security, and ethics, despite being optimistic about the potential benefits of AI," he said.
He added that while 2023 has been a year of mass AI implementation across industries, 2024 will see increased momentum as leaders simultaneously step back and take stock.
For generative AI to reach its full potential — while remaining a safe and ethical technology — business leaders must be looking toward training, investment in policies and collaborative efforts with trusted partners to pave the way.
Related Article: AWS's Diya Wynn: Embed Responsible AI Into How We Work
AI Moves 'Beyond the Sandbox'
2024 will be the year early adopters will go "beyond the sandbox," said Accenture Federal Services' Jennifer Sample.
While a fraction of companies deployed and used products like Microsoft Copilot or Google Bard in 2023, she expects AI's continued rapid development to extend its applications and reach to ever-widening user groups for use in tasks like generative coding and next-gen chat interfaces.
These, she said, will deliver more-relevant information, as retrieval-augmented generation (RAG) surfaces the most accurate and up-to-date context around constituent conversations.
Sample also anticipates a reduction in technical debt and backlogs driven by generative AI augmented work. Augmented work already includes things like assistive scheduling, email triage, day-to-day productivity tools and personalized chat with contextual integration.
Citizen and employee expectations will be elevated as a result, particularly regarding user interfaces. Constituents will increasingly ask for what they want, in simple language, and expect AI to understand and seamlessly assist with their request. This is already coming to life in daily consumer interactions, as various commercial sectors lean heavily into AI's assistive capabilities, she said.
“In 2024, the federal government will be expected to similarly raise its game, leveraging new tools to make workers more effective and productive,” she added.
Related Article: Generative AI, the Great Productivity Booster?
Costs and Environmental Impact Will Shift Generative AI Strategies
The C-suite’s growing recognition of the hidden costs and ecological impact of using generative AI will knock reason back into their 2024 AI agenda, said Maxime Vermeir, senior director of AI strategy at ABBYY.
"They’ll discover that the business challenges they’re facing can be solved with narrow AI applications — 90% of it originating from needing access to, and human-like understanding of, their own data and processes," he said.
Using AI to search and summarize data consumes 10 times the energy of a normal search today, he continued, a practice that is unsustainable and unnecessary for most business cases.
The focus will therefore shift from generative AI to more specialized, contextual AI/ML solutions that address specific business problems effectively, he said. These tailored solutions promise high accuracy and straight-through processing in real-world scenarios. "Unlike the broad strokes of generative AI, specialized AI digs deep, offering precise solutions to complex business problems," he said.
As a result, smaller AI models will rise in prominence to offset energy requirements, opening opportunities for AI companies to guide customers towards more efficient approaches to AI.
Businesses will likely continue to grapple with the trade-off between generative AI capabilities and their ecological impact, he added. However, given the concerns about the carbon footprint of large AI models, we should expect a significant push towards carbon-neutral AI development practices. Vendors producing the LLMs will need to work on optimizing algorithms to be more energy efficient.
Related Article: The Green Potential of Remote Work: Reality vs. Myth
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It's Only the Beginning
Organizations are only starting to scratch the surface of generative AI's potential impact. Wrike's Alexey Korotich believes in 2024 organizations will start using generative AI as a toolkit not only for the business, but for the employee as it pertains to productivity, efficiency and creating space for meaningful work.
“In 2024, I believe we will see organizations make the shift to work with AI in even more meaningful ways. AI will help companies analyze and connect a significant amount of data sources, creating more transparency and providing critical insights that ultimately help teams make better decisions,” he said.
The emergence of citizen developers that we saw during 2023 will continue, enabling employees to take a direct role in helping company leaders and IT drive business agility, innovation and productivity.
Building teams of citizen developers, he added, will help to bridge the gap between the needs of employees and unique requirements of business processes, and allow people to craft dynamic workflows in their natural language without writing code. This will eventually make software development more accessible, flexible and scalable.
From Hype to Clarity
One of the challenges companies faced in 2023 is they knew they needed to do something with generative AI, but struggled with how to use it within their application stack, said Datastax CTO William McLane. “While 2023 was all about 'hype,' I think 2024 will be all about clarity,” he said. “At the core of generative AI is data and as part of the 2023 hype cycle, hundreds of companies started by building chatbots around their data."
While these applications are interesting, the real power of generative AI will enter when we move beyond chatbots and look at bringing together predictive analytics/AI with generative AI functionality, he continued. This includes applications that can predict what is going to happen and more importantly react to the situation in real time and generate a response either via AI-generated code, AI-generated opportunities or AI-generated engagements.
"This is where I think we are going to see the sea-change around generative AI in the future," he said. “We are going to see clarity around the use cases generative AI is focused on and clarity on where generative AI provides value."
Substance or Surface Only? Up to You (and Your Data)
Google VP Gerrit Kazmaier predicts that by 2025 almost all analytics systems will work with and be powered by generative AI. At its core, AI is about offering new insights, whether through analytics or generative content. Either way, success depends on data breath, data quality and data usage, he said.
Otherwise, he said, you've just got a bunch of seemingly clever programs that use AI with no purpose and no substance — and this is more rampant across organizations than many realize, he cautioned. Early movers in the machine learning and generative AI revolutions, he said, have an advantage in speed and efficiency to develop and activate accurate AI models, the key to broad deployment.
“Companies will want to bring AI closer to their analytical systems to draw both generative-based and ML-driven results. Other businesses racing to catch up will be drawn to more powerful and automated data systems built for the generative AI era, modernizing their data systems for better quality, flexibility, and outcomes. Those who wait … well, they'll have a challenging 2025,” he said.