Feature
Generative AI will improve productivity — that's the widespread assumption. And while a few small-scale studies have borne out those claims, the extent and specificities of where those productivity gains will happen is still being established.
Keep in mind, for example, that it's only been 8 months since Microsoft first introduced Microsoft 365 Copilot, which is now available for most of the commonly used Microsoft productivity apps.
A Microsoft report explored these questions last November. While the results should be taken with a grain of salt given the source, they offer a few signs of where and how productivity gains may be felt. The Work Trend Index: Special Report was based on a survey of 18,100 early Copilot adopters in 12 countries across six key workplace functions. The results include:
- 77% of respondents said they did not want to give up Copilot.
- 70% said they were more productive with Copilot.
- 68% said it improved the quality of their work.
- 64% of users said Copilot helped them spend less time processing email.
- Overall, users were 29% faster in a series of tasks (searching, writing and summarizing).
We asked experts where they are seeing the impact of generative AI tools like Copilot in the workplace. Here's what they had to say.
Improving Workflows, Enabling Work
Microsoft was ahead of the curve when it integrated Copilots into its customers’ ecosystems, said Prerna Kaul, associate director of product for generative AI at Moderna. In the case of Copilot for Microsoft 365, the idea is it can help with most workplace tasks within existing workflows and is inherently scalable.
It ensured two important user behaviors related to generative AI and work, she continued. First, global adoption of AI will only continue in an effort to accelerate productivity. Knowledge workers will become accustomed to engaging with AI to provide feedback, inspiration and co-creation on documents, presentations, images, code and more.
Second, people will turn to the emerging open-source large language multi-modal options to explore cheaper, faster and easier solutions to their problems, Kaul said. Accessibility to such powerful tools will drive the need for companies to establish responsible AI tools, to ensure that approved AI tools remain helpful, harmless and honest.
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Treat Copilot Like Other Software: Educate End Users
In most cases, Copilot is incentivizing process change, rather than filling a gap in technology or meeting a business need, Olga Kupriyanova, principal consultant at ISG, told Reworked.
IT teams face similar challenges with Copilot as they do with other software (from both COTS and DevOps programs), particularly challenges around adoption and usage. Awareness and education are needed for any software application introduced to an enterprise.
Some users are already struggling to get value from Copilot (“I don’t understand what it does,” “It didn’t give me useful information,” “It doesn’t apply to my work,” etc.) similar to experiences with the animated paperclip guide Clippy, she said. In light of this, IT should be cognizant of the message it sends to the workforce about trying generative AI tools like Copilot. IT should view this as an opportunity for employee engagement and crowd-sourcing use cases, rather than an opportunity to say “no” to any application that is not officially blessed and supported.
“If we, as industry analysts, learned anything from the rollout of data sciences and machine learning applications to enterprises over the past decade, it is that it is best to involve the workforce in planning and technology trials,” Kupriyanova said. "If the workforce champions an application, the value of the application will be realized. Their experiences will help temper the use cases, the scale of deployment, and the benefits for the organization."
She argues that generative AI and Microsoft Copilot are unique because they have brought AI into the real world, with real world applications. They've also made complex AI technology relatable. When people successfully complete a task with generative AI, not only does their confidence in the technology grow, they also begin to imagine what else it can be used for.“This is the power of generative AI. A lot of the momentum for tools like Microsoft Copilot is coming from actual users and early adopters, and in a lot of cases IT is reacting to the push from its stakeholders rather than the other way around,” she said.
People's Skills Must Evolve With the Technology
In spite of their relative newness, generative AI systems are becoming increasingly adept at identifying and autonomously solving problems, said Inspira.ai co-founder and CEO Izzy Traub. He said workers must adopt a mindset of adaptability and continuous learning to harness the benefits of these early generative AI use-cases, as the skills needed to effectively use the tools will evolve in tandem with the technology.
He insisted there is no evidence yet to suggest that generative AI will replace human creativity and innovation. “Rather, it is a powerful tool that can augment human capabilities and drive productivity to new heights. By embracing generative AI and adopting a continuous learning mindset, individuals can enhance their productivity and position themselves for success in the ever-changing AI-driven landscape," Traub said.
Related Article: Change Management in the AI Age: How to Sidestep Common Mistakes
Ethical Concerns
Not everyone is convinced that organizations should be rushing to deploy large language models.
Workplaces — and broader society — must first face an ethical conundrum: the fact that AI will become increasingly indistinguishable from humans, said Ilia Badeev, head of data science at Trevolution Group.
“Texts written by AI are already indiscernible. Images are close behind,” he said. “Videos will follow in the near future. One of the ethical challenges is that people may not be able to discern where AI ends and human input begins."
An increasing number of work processes (accounting, design, basic software development) already involve AI, either in a collaborative role or being handled solely by AI, he continued. The result is that AI will gradually and relentlessly replace humans in various tasks. It won’t completely displace humans from work, Badeev argued, but it will significantly reduce the number of people needed in an organization by taking over a majority of routine operations.
“At present, it seems that AI won’t create many new professions. The role of ‘prompt engineer’ has become popular recently, but this is a temporary phenomenon born from the imperfections of current AI. Over time, the skill of prompt engineering will become as fundamental as computer or smartphone literacy,” he said.
The best strategy for the moment is to stay informed and approach the discourse surrounding AI with a level head. He compares AI's current limelight to the initial frenzies over the internet and blockchain: As the novelty wanes, AI’s true nature as a very, very powerful tool — not a magical solution — will become apparent.
“However, if you want to come out on top of this wave, the recipe for success is still the same — find a problem that no one else is solving or provide a better way to solve it using new approaches or tools. And be the first to deliver it! This has proven to be true time and time again, with or without AI,” he said.
What Happens to Expertise?
While Gemmo AI founder and CEO Luca Marchesotti acknowledges the potential productivity gains resulting from generative AI use, he warned these advancements come at the cost of potential over-reliance on technology. He points to a growing apprehension that generative AI will stifle creativity by pushing creative minds into autopilot, with the result being a homogenization of previously diverse and nuanced human-derived ideas.
Another risk is the devaluation of expertise and specialized knowledge, he continued. What becomes of experts when an AI model can replicate tasks that once required years of study and experience?
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“As AI takes over more functions, opportunities for hands-on learning may diminish, potentially eroding the skill sets that professionals have traditionally built over time," he added.
The crux of the issue is value — how we assign it and how we preserve it. As AI reshapes the workplace, it is imperative to maintain a balance that honors and values human contribution, Marchesotti said. We must guard against the mindset that if a machine can replicate a task, the human element of that task is worth less. Instead, we should view AI as a collaborator, one that enhances human work rather than replacing it.