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Home » Time To Take The Low Expectations Out Of GenAI
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Time To Take The Low Expectations Out Of GenAI

Press RoomBy Press Room18 January 20254 Mins Read
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Time To Take The Low Expectations Out Of GenAI

Generative AI is not conventional automation — swapping out a human being for software — and should not be treated as such. It would be a waste of time and effort, not to mention an example of low expectations, to pitch genAI as a means to simply automate tasks. Rather, it goes far beyond this role and needs to be looked at as the transformative force it can be that amplifies, not replaces, human work.

Unfortunately, business leaders tend to look at genAI and AI in general as a cheaper way to get things done. Their employees, on the other hand, see something different happening, an analysis published by Accenture relates. Ask employers and employees exactly how AI transformation happens, or what the results will be, “and it quickly becomes clear we are caught in a stare down,” the report’s authors, led by Accenture CTO Karthik Narain, state.

The key is to put people in charge of the direction AI will take with their jobs. Most see the role generative AI can play in assisting and amplifying their work — it can lead to job satisfaction, and career-advancement opportunities.

Generative AI, by its very nature, “is inherently a learning technology. It can enhance and advance its skills over time, ultimately improving its value to the individual using it and to the organization as a whole,” Narain and his co-authors state. “In other words, the more people use it, the better it gets, and then the more people want to use it.”

Their employers, on the other hand, tend to take a narrower view of AI as the route to greater automation. “It’s a situation brewing uncertainty and distrust, and risks holding back the technology’s adoption and potential,” the Accenture team states.

They offer three key avenues for achieving the best results with an AI-savvy workforce:

  • Accessibility of automation: “AI’s growing accessibility is what’s driving bottom-up autonomy in the workforce. While we’ve had no-code/low-code in the past, the adoption and utilization of today’s natural language-driven AI tools is growing far more rapidly and will touch far more types of workforce tasks. The question for enterprises is how to leverage these capabilities and workers’ enthusiasm to reimagine their strategies.” However, at this time, only 47% of executives surveyed by Accenture say they expect their organizations to make genAI tools significantly-to-fully accessible to their employees to automate tasks and workflows over the next three years.
  • Agentic workflows. There’s been a great deal of discussion in recent months about the potential of AI agents to solve complicated cognitive tasks, and this will be a boost to people across organizations. They can serve as “a layer of abstraction across technology, handling lower-level tasks like writing code and connecting pieces together. Instead of employees asking, ‘how can I write this software’ or ‘what software can perform this task,’ they can ask ‘how can an agent help me accomplish my goal?’”
  • Physical copilots. This is an area in which frontline and manual workers will be interfacing with AI. Technologies such as robots, exoskeletons, and drones will be enhanced with AI and genAI to achieve “greater contextual understanding of the world and the ability to take more flexible and general-purpose actions in it.”

GenAI is highly democratized technology which can be used by anyone, the Accenture authors point out. However, they caution, the “pace of diffusion will grind to a halt if people are uncertain about what the future will hold.” The key to AI success is to provide people the freedom to learn and discover how AI can amplify their skills, through “building small automations, finding efficiencies, and seeing which new innovations work and which don’t,” they add. This “will give you a jump start on the future, propelling you far beyond what strict automation ever could.”

Accenture Artificial Intelligence Generative AI Workflow workplace
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