The promise and peril of AI at work in 2024, according to Deloitte's Tech Trends report
The release of ChatGPT in November 2022 unleashed a frenzy surrounding generative artifical inteligence (AI), resulting in the exponential growth and development of the emerging technology through 2023.
Twelve months on and Deloitte's Tech Trends 2024 report takes a deep dive into the events of the past year to help businesses learn how they will be impacted by generative AI during the next 12 months.
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At the end of each year, Deloitte releases its annual Tech Trends report to help business and IT leaders learn about how emerging technologies might impact their businesses, and how to best deploy these tools. Unsurprisingly, generative AI was a major topic of Deloitte's 15th annual report.
Within the first 60 days of ChatGPT's release to the public, OpenAI garnered 100 million users. For comparison, it took TikTok, a major leader in the social media space, nine months to reach that milestone.
The heightened level of interest was likely fueled by how intuitive ChatGPT is to use, allowing everyone, regardless of technical skill, to take advantage of the tech. What's more, the use cases for the chatbot were evident.
"People who have, from their desk and keyboard, watched mechanical muscles automate manufacturing and automate spreadsheet analysis, suddenly, they're finding mechanical minds beginning to automate what they do," said Mike Bechtel, chief futurist with Deloitte and co-writer of the report. "I think that's why this arcane evolution of transformer models has become a bonfire of interest among gen pop."
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Business leaders' interest in the technology parallels that of the public, with 80% of business leaders in a Deloitte CEO survey from summer 2023 agreeing that generative AI will increase efficiencies in their organization.
The generative AI promise
Generative AI is an extremely capable and intelligent technology, and, as highlighted in the report, can oftentimes outperform humans.
For example, ChatGPT scored a five out of five on the Advanced Placement biology exam, and Anthropic's Claude 2 chatbot scored above the 90th percentile in the verbal and writing sections of the GRE exam.
These capabilities have led many employees to panic about generative AI replacing them in the workforce. However, according to the report, there is no real indication that business leaders will want to automate knowledge jobs on any scale.
"One of the patterns we've seen over the years is this phrase we often use, 'you can't shrink your way to success,'" said Bechtel.
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Bechtel then went on to explain that there typically are two camps of leaders: the short-termists who see emerging technology as a crash diet, a way to do the same thing with fewer people, and the long-termists, the ones who want to use emerging tech to make work better. It's the latter group that sees the most success.
"I think the entrepreneurs are going to separate themselves from the rest because they're going to use this as rocket fuel for elevated ambitions, as opposed to a license to skinny up," added Bechtel.
Other research comes to similar conclusions. An IBM survey showed that the most common use cases for generative AI that business leaders prioritize include improving content quality, driving competitive advantage, and scaling employee expertise over reducing headcount.
The Deloitte findings also conclude that the real opportunity for harnessing generative AI in organizations lies in using the technology to optimize business operations, rather than reducing headcount.
"The true value of generative AI is likely to be unlocked when organizations can use it to transform business functions; reduce costs; disrupt product, service, and innovation cycles; and create previously unachievable process efficiencies," said Deloitte in the report.
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In every one of the above use cases for the optimization of business operations through generative AI, not only would the enterprises as a whole benefit, but so would each employee's workload.
For example, if a business leverages a generative AI model to take all of its data and compile it into a searchable database, that process positively impacts everyone in the organization as much as it benefits the organization's operations.
But while the replacement of knowledge workers might not be a major negative impact of generative AI, there are some significant risks involving the use of the technology that business leaders must prepare for.
The risks, and how to tackle them
Generative AI's ability to imitate human dialogue and reasoning means the technology can be employed by bad actors to efficiently accomplish harmful tasks, such as cybersecurity attacks, which pose a huge risk to enterprises.
According to the Deloitte report, phishing is the most common cyberattack, with 3.4 billion spam emails sent every day. Thankfully, many of these attacks do not succeed because recipients can detect flaws, including poor grammar and spelling.
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Generative AI applications, such as chatbots, can create legitimate-looking malicious content at the command of a simple prompt, eliminating syntax errors and making it harder for people to distinguish real from fake.
Beyond text, Generative AI could also be used to create malicious content across many different mediums, including voice and even video.
"The trend that we've uncovered in Deloitte Tech Trends is the bad guys have AI too, and specifically, they're using AI to exploit the most vulnerable point of most companies' stack, which is the human," said Bechtel.
All of the most advanced protections can be rendered useless if a worker willingly hands over a password.
For example, deepfakes have been used to attack businesses by impersonating the voices of business leaders within the company. Scammers used this technique to swindle $243,000 from the CEO of a UK-based energy firm, as highlighted in the Deloitte report.
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The world of cybersecurity involves a constant game of cat and mouse, with defenders finding new ways of protecting themselves as attackers get smarter and find new ways to attack. As part of that ever-evolving process, new ways for users to protect themselves from deepfakes will evolve in the near future.
But until then, what do you do? The advice from the expert: don't trust what you hear and see.
"Don't believe your eyes. Don't believe in ears. In math we trust, in cryptography we trust," said Bechtel.
"Whether that's an individual making sure that an email they've received is from the company, or it's an enterprise-wide organization, investing in zero trust in cyber defense, that's really the best advice. We can't believe our own eyes."
How to approach
Given the range of positive and negative impacts of generative AI, you might be left wondering exactly how you feel about the technology.
Bechtel says the answer to that conundrum is found in striking a balance between both ends of the spectrum.
"Hyperbole in both directions is the problem," said Bechtel. "Wide-eyed enthusiasm and grumpy skepticism aren't helpful; what's helpful is figuring out how to leverage these tools in a way that's merely very useful."
To help businesses prepare adequately to leverage generative AI in a beneficial way, the report delineates different areas where companies can focus their attention.
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The first way involves the upkeep of enterprise data. Generative AI models are trained on robust amounts of data, which can then be used to execute a series of actions, such as creating a searchable database.
However, to complete that process effectively, or any of the next-generation use cases, businesses need to ensure their data is architectured properly and is accessible to AI applications, according to the report.
Another important aspect to keep in mind while adopting generative AI is governance. Generative AI, as intelligent as it is, is prone to hallucinations or other missteps that could put the business at risk.
As a result, businesses should preemptively establish proper guardrails to prevent mishaps from happening and to ensure prime performance.
"Without effective governance guardrails, AI can't scale," said the report. "A governance framework should define the business's vision, identify potential risks and gaps in capabilities, and validate performance."
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Lastly, the report highlights the need for businesses to implement generative AI step by step, without rushing the process. Specifically, it recommends the approach: crawl, walk, run, and fly.
"This approach has for years been an effective way for enterprises to scale up their use of service offerings," says the report. "Generative AI is no different."
In the "crawl" stage, the applications require a lot of manual effort. But as the applications graduate through the next stages, they become more refined, culminating in the fly phase, when an organization can reap the rewards from their work.