Leaders Must Rethink Productivity In The Age Of Generative AI

Generative AI has shown the potential to transform more than 40% of working hours. This shift represents a fundamental change in how we work, the skills we will expect from our team members and the amount of time we can reinvest elsewhere. It provides an opportunity for C-suite leaders to reconsider how they measure productivity, how their companies can become more competitive in the current economic environment, and ultimately, what’s needed to drive future growth.

How will this change the ways business leaders deploy human and financial capabilities? And what does it mean for the workplace? Business leaders are currently facing an environment with resource shortages, supply chain breakdowns, shifting consumer demand and other uncertainties that can often lead to a narrow, short-term response. Historically this meant putting efficiency at the top of the list, instead of viewing these situations as an opportunity to think long-term and be strategic about establishing a resilient future for their businesses.

The world’s leading companies, however, are those who successfully look to the latter for growth. Those leaders are focused on how emerging technologies, data and AI, including generative AI, are enabling improvements in productivity in ways that might not have been possible before. At a time when balancing financial and human capital is a given, these businesses understand that technology can allow us to think differently and act bolder.

Accenture recently analyzed generative AI’s potential to impact productivity across 19 industries and found that for specific industries, the potential productivity gains can be anywhere from  9% for natural resources all the way to a 30% gain for banking. For instance, a consumer-packaged goods manufacturer – an industry that could see a 9% gain in productivity – experienced workforce shortages and concerns about attracting new talent, on top of facing operational inconsistencies that were costing time and money. The company brought in new leadership that embedded automation into many of its processes to create consistent operations across its plants, which led to increased productivity.

There are already additional use cases and applications of generative AI featuring the human and machine collaboration:

• In retail, generative AI can help meet consumers’ changing demands by offering hyper-personalized shopping experiences, digital commerce, operations and customer service. Businesses can use the technology in their supply planning, product design and merchandising, among others.

• In financial services, generative AI can streamline front and back office by acting as a co-pilot for underwriting or claims adjudication, or even help recommend investments as an intelligent wealth advisor. ­­

• In industrial manufacturing, the technology can be used to manage assets and capital projects through augmented asset management, fielding force enablement and augmentation. It can accelerate generative design or be used as a co-pilot for safety audits and incident response.

As these examples highlight, technology is accelerating step changes in productivity that improve customer and employee experience, increase capital efficiency and strengthen business resilience. Considering that its disruptive potential is still in a nascent state, how can leaders prepare to usher in this new?

First, executives will need to ensure their companies have the right data structures, operating models and skills to make the most of generative AI – all of which needs to be underpinned by a responsible AI framework that accounts for potential biases, security and privacy risks. Second, they’ll need to rethink the meaning of productivity:

• Leaders must shift their focus from work as transactional to being productivity-led, creating value for customers, employees, society and other stakeholders. This requires thinking long-term about what skills a company will need to be successful in the future, and continuously reevaluating where resources are allocated to ensure they are aligned with the company’s strategic priorities and delivering 360-degree value (focusing on financial and non-financial metrics).

• Generative AI is challenging notions of work as companies rethink what needs to be done and how it gets done, rather than being stuck in stagnant processes. For instance, companies often assign people early in their careers with mundane tasks like manually gathering or entering data – missing a key opportunity to empower their employees. Instead, leaders should consider creating a center of excellence for data and analytics that would give employees at all levels visibility into data across the enterprise to help them make strategic insights, which has the added benefit of supporting an employee’s career growth.

• Strong leaders know that their people are one of their strongest assets, and it’s imperative that employees have the ability, opportunity and motivation to succeed. Take a page from a chemical company that wanted to preserve a sense of entrepreneurialism, adopting a co-ownership of costs and growth investments with its people, including sharing financial information. The company organized virtual collaboration workshops, training sessions and leadership coaching programs to hardwire this thinking into its culture.

This is already happening right now for those willing to rethink and reimagine how work needs to get done, rather than focusing on how it’s been done— and others should follow suit. In a sign of what’s to come, we’ve also found that nearly all (94%) C-suite executives anticipate increasing their technology spend in the next year, and a quarter have reported daily usage of generative AI tools in their professional activities. This is a welcome sign, but what will set today’s leading companies apart from yesterday’s leaders is how they can use technology tools at their disposal to successfully reinvent work and productivity.