Where Will Generative AI Produce the Biggest Productivity Gains?  

Where Will Generative AI Produce the Biggest Productivity Gains?  

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Following substantial developments and improvements to large language models (LLMs), Generative AI has surged to the forefront of the business world, capturing the imaginations of business leaders and sparking strategic conversations about harnessing this technology to drive growth and competitive advantage. McKinsey’s research estimates that Generative AI could add the equivalent of $2.6 trillion to $4.4 trillion USD to the global economy annually, with 75% of this value delivered across the areas of customer operations, marketing and sales, software engineering, and R&D. To put this into perspective, the UK’s entire GDP for 2022 was just over approximately $3 trillion USD (£2.27 trillion GBP).

Other experts including the World Economic Forum, BCG, PwC, and Gartner have championed Generative AI and its potential to reshape business as we know it. Organisations who have already adopted are reporting benefits to their productivity and effectiveness. But where are the biggest gains to be found? Our research has identified the following key areas as having the most potential for reaping Generative AI’s benefits:

• Efficiency: Augmenting and streamlining business activities is by far the most cited use case for businesses looking to adopt Generative AI or already using it in their teams. Because of improvements in LLMs, Generative AI is estimated to have the potential to automate work activities that consume between 60% and 70% of employees’ time, with 50% of daily tasks to be automated at some point between 2030 and 2060. This might include activities involved with communicating with and engaging customers and prospects, producing reports, generating marketing content, managing performance, and so on. It is likely that these gains will be the driving factor when senior executives, C-suite leaders, and board members debate Generative AI adoption. But efficiency gains may come with a human cost, and senior leaders will be tasked with rethinking their human labour needs. Redefining roles and responsibilities will be a major challenge faced by senior leaders, as they will have to consider where their human talent can best generate value and impact when working alongside the digital workforce.
• Creativity, Strategy, and Innovation: However, one benefit of Generative AI automating routinised, mundane, or time-consuming tasks is that this frees up human staff to focus on tasks with a higher value-add. Most often, these will be tasks that favour human intelligence that cannot yet be replicated by technology such as creativity, strategy, and innovative thinking. While Generative AI is a major asset in creative tasks, it still requires a human prompting it to produce the desired outputs. AI can glean insights and business intelligence, but it cannot apply contextual relevance to that information and use it to develop innovative strategies, at least not without a human steering it to do so. By leaving Generative AI to handle to tactical execution, senior leaders are freed up to do the high-level thinking that will guide this activity. It is likely that organisational effectiveness in delivering strategic priorities, creative projects, or value-add initiatives will be enhanced as a result.

That said, this may come with a caveat. A study conducted by BCG with the support of a group of scholars from Harvard Business School, MIT Sloan School of Management, the Wharton School at the University of Pennsylvania, and the University of Warwick found that when using Generative AI for tasks involving ideation and content creation, around 90% of participants improved their performance on a level that was 40% higher than that of those working on the same task without AI. But when using Generative AI for tasks related to business problem solving, participants performed 23% worse than those doing the task without AI. These results reinforce the idea that both Generative AI and human intelligence have their own areas of value creation, but the study also found that there are risks to relying on Generative AI for creative tasks long term. For instance, Generative AI enhanced creative performance but produced outputs that were fairly repetitive, with the diversity of ideas among participants who used AI 41% lower compared with the group that did not use technology. Over time, it is feared that over-reliance on Generative AI will stifle creativity, with 70% of participants sharing this belief.

To combat these adverse effects and truly reap the benefits of Generative AI for creativity, innovation, and strategy, senior leaders need to guide their organisations towards AI integration that enhances performance rather than stifling it. The challenge will be implementing Generative AI without creating an overreliance on it and building successful partnerships between man and machine. Understand where AI thrives and where humans have the advantage, and design activities around those core competencies.

• Learning: As the business landscape transforms, skills and capabilities must adapt alongside it. At the same time, Generative AI and other technological advancements continue to evolve, creating a continuous learning curve. Most senior leaders will need to upskill in the coming years to continue delivering value in the Generative AI-powered world of work. Thankfully, Generative AI can assist in these efforts. Adaptive learning platforms tailor upskilling and training initiatives to individual users, helping senior leaders target their specific needs and hone their skills in a format that maximises retention and learning performance. Just as we learn, so do AI algorithms. They are trained on vast amounts of data and the more we use them, the more knowledgeable these tools become over time. Outside of an intensive upskilling programme, Generative AI platforms like ChatGPT and Bard can be massively helpful for researching different topics. However, be aware that these LLMs are only trained up to certain points in time and may struggle with more recent events and developments.

In addition to benefitting from Generative AI in their own continuous learning activities, senior executives can expect to see productivity gains when training, reskilling, and onboarding their people. Generative AI can automate learning and development activities to equip teams with necessary skills quicker and more effectively through adaptive learning. Tailored learning experiences are more engaging and interactive, with the knowledge delivered more likely to be retained. This will result in time and cost savings for the business.

This is only just a flavour of what Generative AI can and will do for businesses and their leadership. As this technology evolves and becomes more advanced, it is likely that we will see more creative and strategic use cases arise, with new gains in efficiency and understanding as a result. The key thing to keep in mind, however, is that Generative AI is not a fix-all. There must be a balance between human capabilities and artificial intelligence to maximise the impact and value-add of both parties in the workforce. Senior executives will have a critical role to play in structuring how and why their organisation uses this and other technologies moving forward.