The unknown in the workplace: Generative AI challenges for CIOs

Ensuring that organizations form productive partnerships with increasingly intelligent software tools is key to the success of a generative AI strategy and requires guidance and guidance for both parties. This partnership will ensure that end users can leverage the full potential of smart tools and realize synergies. Therefore, organizations should actively participate in and promote the establishment of such partnerships to ensure that both parties can promote and support each other to achieve common goals.

In the rush to develop technology strategies to deliver on the promise of generative AI, many CIOs are finding themselves stuck in what may be their most challenging task yet: preparing their organizations for their end users. , these users range from knowledge workers and assembly line workers to doctors, accountants, and lawyers. They need to coexist with generative AI and ensure its smooth integration into workflows.

While large-scale language models and tools like Microsoft Copilot are viewed as assistive rather than worker-replacing technologies, the proliferation of generative AI products on the market and the rapid implementation of these models has challenged this view. A challenge was posed. These tools are capable of performing many human tasks in production environments, revealing the complex relationship between AI machines and humans. As a result, many analysts, thought leaders, manufacturers and CEOs believe that AI technology must work closely with humans rather than replace them.

Reuven Cohen, strategic AI advisor to Fortune 500 company Baxter International, pointed out that the risks of generative AI are high given its disruptive potential.

He said: "The debate is between augmenting the workforce or replacing it entirely. First, the most capable people in the organization can be supported through customized AI; then, the less capable people can be phased out."

However, the definition of “less capable” may be affected by technological developments and the development of human-machine partnerships in areas where the technology is implemented. This is because as technology advances, the capabilities of generative AI are also constantly improving, which may make humans who do not use generative AI appear to be less capable in certain aspects. However, it needs to be clear that generative AI will not completely replace humans, but will cooperate with humans to provide more efficient and intelligent solutions. As Teradyne CEO Shannon Gath said, “Humans using generative AI will replace those who don’t.” Therefore, people should actively adapt and master generative AI technology to improve their capabilities and competitiveness.

Currently, the vast majority of CIOs are adopting generative AI to improve work efficiency and productivity. According to Gartner, 77% of CIOs have already begun deploying this technology. Jamie Holcombe, chief information officer of the U.S. Patent and Trademark Office, is one of them.

Holcombe believes that AI is an enhanced intelligent tool. He does not believe that there is a cooperative relationship between people and tools, but a usage relationship. His reviewers welcome the help provided by AI tools to relieve them of the burden of paperwork and administrative work, allowing them to focus more on thoughtful analytical work rather than just programming work.

Therefore, one of the CIO’s top priorities in 2024 is to explore and uncover the unknown added value that human workers can bring by leveraging large language models.

Mike Mason, chief artificial intelligence officer at Thoughtworks, believes that in light of this problem, it remains critical for CIOs to consider providing new generative AI tools to their employees.

"Even as AI becomes more advanced and integrated into software and daily tasks, the influx of AI tools still creates confusion for employees. CIOs must remember that those using this AI technology are their employees, but also taking into account the impact of AI on their employees, ensuring appropriate management, training and integration to make the most of their investment.”

Formation of Close Partnerships

Despite calls from well-known industry figures to be cautious about AI, most corporate giants, including Goldman Sachs, Fidelity Investments, Procter & Gamble, American Express, Gilead Sciences, etc., have publicly stated that they will develop and deploy large-scale language models internally to improve Productivity and innovation.

Vipin Mayar, head of artificial intelligence innovation at Fidelity Financial Services, said at the Chief Artificial Intelligence Officer Summit in Boston in December that early returns have proven to be fruitful for cost savings and efficiency gains.

While Mayar admits that large language models are not comparable to human intelligence, he believes that the pace of innovation in generative AI is unparalleled. “It’s only been 13 months, and it makes time non-linear,” he joked. Still, to ensure workers get the most from these tools, Mayar recommends Multimodal large-scale language models that combine structured datasets and unstructured data are designed to be smaller and task-specific.

Yvonne Li, vice president of artificial intelligence, data engineering and decision science at Advanced Auto Parts, agrees that the technology — and how humans can leverage it — is still in its early stages.

“AI is not a panacea, generative AI can bring data together and give data scientists a different perspective, but it cannot make ideas for us. People are using AI to improve efficiency and as a tool to diagnose problems ."

Thomson Reuters is an organization that aims to improve efficiency with artificial intelligence. The company recently released a generative AI platform that makes it easier for developers to create solutions such as AI-Assisted Research on Westlaw Precision. Shawn Malhotra, head of engineering at Thomson Reuters, said Westlaw, which uses generative AI technology, enables legal editors to generate document summaries for legal research in minutes, which would have taken days or weeks to complete in the past.

In addition, there is legal drafting work by Thomson Reuters and Microsoft Copilot, unlocking more advanced features for legal editors. But observers say such innovation will require CIOs to develop upskilling and governance strategies to ensure employees can benefit from new generative AI wherever they are. This will soon become critical as the drive for productivity increases puts pressure on employees across the enterprise to learn to work with large language models, many of which are still in the pilot testing phase.

"Large language models can and will surpass human capabilities in many ways, but I firmly believe that AI will continue to augment human capabilities," said Deloitte U.S. resident CIO and former global CIO at Vanguard Group Officer John T. Marcante said. "I think AI will be a very close companion of humanity now and in the future."

Marcante emphasized that in order to ensure a friendly relationship, it is important to consider stakeholder workflows when implementing generative AI. .

"It's important to remember that using AI to speed up outdated or burdensome processes may be a mistake. More benefits may come from process or technology improvements rather than widespread application of AI to 'solve' problem," he said.

Changing the way work is done

Over time, technology and the way it is used evolve and change, which will inevitably change the way people take full advantage of these tools.

At the recent CES, Accenture issued a public statement saying that generative AI tools are more "humane" in design, especially exquisite conversational user interfaces, robots that respond to English commands, and Software that enhances the natural way humans work, such as Adobe Photoshop’s Generative Fill and Expand feature.

At the end of last year, Gartner introduced in detail how generative AI will completely change the relationship between humans and machines at the IT Symposium/Xpo annual conference.

Gartner analyst Mary Mesaglio said: "This is not just a technology or business trend, but really a shift in the way we interact with machines. We are moving from what machines can do for us to what machines can do for us. What it can be for us. Machines are evolving from our tools to our teammates."

Mesaglio said machines are evolving not only into work partners, but also into customers. For example, HP printers can buy ink when needed after being connected to a service that monitors usage levels, and Tesla cars can order parts when self-diagnostics reveal a fault.

The USPTO’s Holcombe also believes that the development of interfaces will help employees use these tools more effectively, and that the next generation of human-computer interfaces will be natural language rather than keyboard and mouse. But he still believes that large language models will not replace human cognition anytime soon.

“Human thinking and analysis have not yet been surpassed by machines, because the algorithms themselves are at best iterations of guesswork and trial and error. I have never seen a machine make an intuitive leap without human programming. .”

Usama Fayyad, executive director of the Institute for Experiential Artificial Intelligence at Northeastern University, believes that conversational artificial intelligence is becoming more and more important in enterprises, and over time, it can provide solutions to problems Provide more substantive answers. Content generation, document summarization, and augmented analytics and insight extraction tools and decision-making algorithms that require human augmentation will also become important use cases for enterprises across industries, he said.

But in order for these tools to reach their full potential, how and how often humans use them becomes very important. This is the nature of technology.

Joe Atkinson, chief product and technology officer at PwC US, believes that generative AI applications can help create a more tech-savvy workforce, but it is unclear how employees can add value to the tools themselves. , these tools are designed to learn while working. He said there is no doubt that human creativity is necessary to improve the quality of applications.

To this end, Gartner recommends that CIOs establish "lighthouse" principles that define how workers and machines will interact in the next year—a priority Gartner believes is relevant to achieving data AI readiness and implementing AI readiness security Sex is equally important.

After all, generative AI is not a one-size-fits-all tool—at least not yet—and requires human oversight and experience to ensure accuracy, quality results, and safety.

To this end, CIOs are preparing education and training courses to gradually introduce generative AI tools into the workplace and give people confidence to use them.

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