The most successful companies today are increasingly viewing productivity through a broader lens.

High on their agenda are strategic investments, talent development, and the integration of cutting-edge technologies such as generative AI.

To understand how high-performers redefine productivity as a critical metric, we spoke with Chris Roark, Senior Managing Director, Accenture Strategy and Global Lead for Cost & Productivity Reinvention.

In this Q&A, Roark shares insights from extensive research involving approximately 1,400 companies worldwide. He explains what makes top performers stand out, how they balance cost management with long-term growth strategies, and why building a strong digital core—complete with AI and data capabilities—is essential for sustained productivity gains.

What are the primary drivers behind the stark contrast in productivity growth rates among companies today?

We set out to understand what percentage of businesses were experiencing productivity growth year over year, and after an analysis of about 1,400 companies globally, we found that the top 25% of companies were growing their productivity by more than 8% annually.

What set these “high productivity growth companies” apart was a clear focus on investing strategically for future growth.

These leaders view productivity as a growth driver and enabler of innovation, not just an exercise in cost management. For example, they are investing in upskilling and retraining their employees and using technology including generative AI to both speed up and improve quality of tasks.

For every dollar spent, these leaders are creating more value within their teams and across their enterprise.

Also Read: AI productivity: Small changes, big impact

What specific strategies do high-performing companies use to achieve over 8% annual productivity growth?

Companies that achieve high productivity growth are embracing a broader definition of productivity that looks beyond cost management and focuses on what we’re calling the productivity growth equation.

This approach not only considers cost inputs and the actions a company takes to reduce costs, but also an effectiveness factor or actions like reskilling or technology investments that change how work is performed, as well as the multiplier effect of generative AI to improve quality of work and save time to complete tasks.

These leading companies are focused on knowledge-intensive areas of the value chain that offer significant opportunities to improve not only cost, but also speed, quality and innovation, which are critical in today’s highly competitive, tech-driven economy. We call this knowledge productivity.

How are these companies balancing cost and productivity reinvention with growth in revenue?

Adopting a cost and productivity reinvention mindset is synonymous with focusing on growth in revenue. In the last eight years, we’ve seen leaders’ focus on cost fall from 57% to 38%, while at the same time, they’re paying more attention to innovation and technological investments. Conversely, the majority of companies that have seen low productivity annually are still focused on cost management.

And as I mentioned before, our data shows that for every 1% increase in costs, these companies are seeing 1.3% revenue gains. Their leaders are focused on the long-term—they are strategically investing for the future by prioritising their talent and using generative AI as a multiplier to boost their competitiveness.

Generative AI promises significant productivity gains. In your experience, what are the key strategies companies are leveraging this technology?

Companies that are leading the way in productivity are using technology like generative AI as their partner in growth. Generative AI has the potential to impact over 44% of working hours according to our latest estimates. And for this research, we took that a step further to better understand how generative AI can impact specific tasks.

Our modelling suggests that generative AI can improve the quality of work, in addition to providing time savings. For instance, business analysts saw a 23% improvement in the accuracy of their financial and logistics projections by using generative AI to analyse complex datasets. They also saw 18% improvement in the clarity of their communication.

In more creative and judgment-intensive roles, such as customer interactions and problem solving, generative AI has been shown to boost creativity by 130% for employees addressing customer queries by phone, enabling more complex-problem solving.

Software developers saw a 54% improvement in the accuracy of their work when debugging and fixing coding issues.

Also Read: AI in the workplace goes beyond productivity

What challenges do companies face when trying to implement generative AI for productivity improvements and how can they overcome them?

A major challenge for companies is not adopting a people-centred approach to generative AI implementation and addressing the talent and skills requirements associated with this type of effort.

We’ve seen companies operate with a more siloed mindset by investing in technology without also investing in their people. Instead, companies need to adopt an approach of continuous learning and building trust among teams, including by skilling and reskilling employees to ensure they can both see the value in and make the most of the tools at their disposal. For example, executives from high productivity growth companies were 33% more likely to view training as a key enabler of productivity.

On another level, many companies have a difficult time keeping up with fast-moving technology changes in AI and generative AI. To address this gap, leaders need to help their companies build a strong digital core with cloud, data, AI and security. They should also partner with AI experts and ensure they are embedding responsible AI throughout the process. In our experience, we’ve found that relying on poor generative AI setups often results in unreliable or subpar outcomes.

What lessons can companies with low productivity growth learn from their higher-performing counterparts?

The key lessons executives should take away from high productivity growth companies are:

• Shifting their mindset regarding productivity away from traditional cost-management measures to embracing productivity as a path to growth, innovation and competitiveness
• Investing deliberately and strategically to drive revenue
• Emphasising a culture of continuous learning with people at the centre
• Exploring technology like generative AI to multiply their efforts
• Embracing change and breaking through barriers

Looking ahead, how do you see the role of technology and AI in shaping the next wave of productivity improvements?

AI and other technology will be essential in shaping companies’ productivity moving forward. While we see generative AI saving time on tasks, this is just the beginning.

The greater value is in how generative AI can significantly improve the quality of tasks, like increasing creativity in answering customer questions for employees in those judgement intensive roles or leading to better debugging for software developers.

Leaders of productivity growth companies are already encouraging this effort: We found that they spend twice as much on IT per employee as their less productive peers and grow their spend three times as fast.

This new era of productivity will require business leaders to invest in technology, particularly in AI and data, reskill people to gain the technology fluency needed to build a competitive edge and maximise efforts, and partner with leading experts in the space—all of which can help set themselves apart from peers.