Ecosystem innovation series Generative AI: From promise to practical application

When it comes to generative artificial intelligence (AI), we are racing up the hype curve. Now is the time for business leaders to be proactive. So, how do we turn the promise of the possible into practical applications that put people first?

The world’s best generative AI systems can pass legal and medical exams, write poetry, win photography prizes, cut computer code, and chat with such fluency that they pass the Turing test.

But beyond the buzz, there is a gap between the promise and reality of what AI models can do today, although that gap is reduced every day. It can be confusing to understand how generative AI differs from the AI we’ve been using for many years and whether it operates as a digital mind with super-human capabilities and human-level consciousness.

Generative AI is the latest development in a long history of statistical and analytical development.

Generative AI uses deep learning models to write great marketing copy, edit images, solve equations, and draw reasonable diagrams based on data it is trained on. Generative AI tools can surface knowledge without people having to sift through thousands of documents. However, an AI system’s ability to generate content does not mean it has human intelligence. An AI system can be programmed to answer confidently, but a person is always needed to consider the correctness of that answer and how to best apply it.

The extraordinary potential of generative AI tools lies in their ability to analyze the treasure trove of data that every business has buried in their systems and to use that data to unlock new business value. So, let’s look at some use cases.

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Opening doors to business transformation

EY teams work with an ecosystem of alliance partners, including Microsoft, SAP, and ServiceNow, to provide the right technology to help clients create long-term value and transform at speed and scale. (If you are interested in learning more about SAP and ServiceNow, read the other articles in this series from my EY colleagues Kellie Simpson and Chee Kong Wong.)

EY has recently harnessed Microsoft Cloud and Azure OpenAI technologies to develop the EY Intelligent Payroll Chatbot. This tool analyzes individual payslips in the context of regulatory compliance and company policies to answer granular questions and generate personalized explanations for employees. Initial results from the chatbot pilot suggest a 93% first-time answer ratio.

Another powerful application that is just beginning to emerge is in higher education. After the overnight pivot to online learning during the pandemic, many universities were missing the digital spine they needed to deliver a consistent experience to students. EY Learning Lab tool uses generative AI to sift through existing content – from videos to blogs to quizzes to lecture notes – making corrections, filling in learning gaps, and creating new resources. The application is built on top of Microsoft technology and provides a rich, tailored, and consistent student experience.

These examples are three of thousands, limited only by a person’s imagination, that enhance the experience for both customers and employees.

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From hype to reality in four steps

Generative AI's true potential is yet to be realized. But with its future in our hands, the responsibility to develop ethical, empowering, and human-centered solutions is one we all share. But where do business leaders begin?

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1.??? Put yourself out there, and try the technology

Traditionally, technology was the domain of the IT team. But you don’t need to be a data scientist to experiment with generative AI tools. Any employee with an internet connection and a creative mind can start playing in the sandpit. This is exciting.

While it can seem overwhelming, AI tools are easy to use, and playing with them is a great way to become familiar with their potential. Try it; you will start to understand where this technology can take you and open your mind to possibilities for your business.

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2.??? Start with your strategy

Generative AI is seemingly simple and amazing in the speed at which it delivers results to random requests. But it also opens the door for potential organizational chaos unless business leaders act fast. Boards and C-suite leaders can’t afford to wait another day to develop a business-wide AI strategy. AI is not a trend; it is here to stay and will open up new and previously unimagined areas of opportunity.

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3.??? Focus on opportunities first

The technology hype curve is well-worn. The initial excitement and inflated expectations inevitably make way for a messy period of moral, ethical, legal, and technical dilemmas, and disillusionment sets in. We know this will be true for generative AI because we’ve been here before.

We’ve also learned how to get through the disillusionment to uncover real value. The way to do this is to focus on solving business problems rather than deploying technology because it’s there. By first defining the opportunity to deliver real value, you can then seek out tools and partners to help you make breakthroughs above incremental improvement.

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4.??? Put people at the heart

Goldman Sachs has estimated that AI could partially automate two-thirds of occupations in the US. On the other hand, 70% of Microsoft’s latest Work Trend Index respondents said they would delegate as much work as possible to AI. The current uncertainty around generative AI is even more reason to have a comprehensive plan to train employees, identify risks, implement rules, and measure and monitor progress. AI can uplift the capability of people and enhance creativity – but only if we put humans at the center.

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The headlines only hint at the possibilities ahead. Forrester predicts AI spending will hit US$64 billion by 2025 – a doubling in just four years. The questions around generative AI tools – from accuracy and in-built bias to misinformation and job displacement – are legitimate. No one has all the answers, but that doesn’t mean any company can take a wait-and-see approach. The key to success with generative AI lies in strategic foresight, a focus on real-world solutions, and a commitment to placing humans at the heart of every implementation.

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The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organization or its member firms.

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Consulting at EY is building a better working world through the power of people, technology, and innovation. EY member firm partners Chee Kong Wong, Kellie Simpson, and Kerrie McGrath contributed to this series. To read more thought leadership and news about our ecosystem, please follow EY Ecosystems on LinkedIn.

Kellie Simpson Chee Kong WONG Samantha Wong Steve Bingham Will Duckworth Edward Chang Anna Vatandoust Chang-Ho (Hori) Lee Anindo Dutta Tracy Taylor Darren Simpson James Bradshaw Santosh Nair Kellie Pearson Jitendra Patil Pritpal Singh Piyush Kumar Neil Cherry Jeffrey Watts Iain Burnet