GenAI isn’t just eating software, it’s dining on the future of work

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Unlike most other technological breakthroughs in our history, Generative AI has caused a tidal wave of excitement and fear in our personal and business lives.  In many ways, it feels like it’s 1998 all over again when the early days of the Internet dominated the lion’s share of both business and tech conversations and became embedded into the fabric of society.

While AI has been a fundamental part of our technological landscape for over a decade, GenAI represents a substantial leap forward, revolutionizing the way that we work, learn, and interact with technology and one another – especially the major enhancements between the ChatGPT 3.5 version that was launched last November and the recent upgrades to GPT4.

We caught up with someone who’s been a bastion of AI for well over a decade now, Paul Daugherty, the Chief Technology and Innovation Officer at Accenture, on the potential impacts of GenAI on enterprises and the workforce.  Paul has been CTO of Accenture for over a decade and became Chief Executive of the $60bn firm’s technology business in are some key insights from our discussion!

GenAI isn’t just eating software, it’s dining on the future of work

In this evolving landscape of technology – a new paradigm is dawning, one where GenAI is not just impacting how we use technology; it’s fundamentally changing the nature of work. As Paul aptly put it, “We used to talk about how software is eating the world, and now the new analogy is that generative AI is eating software, which means that we have much more powerful ways of interacting with technology than we had before, which stands to benefit the way we work.”

In this reality, it’s not just an incremental improvement on existing AI capability but a leap that has the potential to fundamentally alter our approach to work. While previous technological advancements optimized and streamlined processes, GenAI seeks to redefine the very nature of what organizations do and how they do it. “Whether it’s reimagining content creation in media companies or streamlining regulatory filings in financial and life sciences institutions, GenAI is about reshaping enterprises’ core processes and workflows.” It empowers organizations to rethink how they function – making it a game-changer in the tech landscape.

We’re entering an era of ‘no-collar’ jobs—where AI and humans collaborate to create new jobs

As we step into this transformative era, the concept of “no-collar jobs” takes center stage. Paul introduced this idea in his book “Human + Machine,” where new roles are expected to emerge that don’t fit into the traditional white-collar or blue-collar jobs; instead, it’s giving rise to what he called ‘no-collar jobs.’ These roles defy conventional categories, relying increasingly on digital technologies, AI, and automation to enhance human capabilities. In this emergence of new roles, the only threat is to those “who don’t learn to use the new tools, approaches and technologies in their work.”

While this new future involves a transformation of tasks and roles, it does not necessitate jobs disappearing. To Paul, AI isn’t replacing us; it’s giving us superpowers in our own domains. While technology can streamline the workforce, history has shown it often enables people to work more efficiently. According to an Accenture study, approximately 40% of working hours across industries will be impacted in some way by GenAI, but “that doesn’t mean that 40% of jobs go away because, in most cases, GenAI is impacting a part of a task somebody does.  It’s making their overall job more effective, and often more fulfilling by removing some of the detailed work they needed to do – that can now be done by AI.”

In this reality, reskilling is a critical mandate. Paul emphasized the need to develop both AI development and AI usage skills are critical.  He encourages companies to set up dedicated training academies and learning processes to help reskill their employees.

Paul’s predictions point to the next epoch of enterprise evolution

When asked to peer two years into the future, Paul made four predictions about GenAIthat signal a seismic shift in the evolution of the enterprise – alongside some cautions:

  • Accelerated Experimentation and Scaling: In a year, companies will shift from experimenting to scaling AI solutions, with more focus on specific use cases for widespread deployment. Traditional enterprise software companies will increasingly incorporate generative AI into their products, making it a standard part of operations.
  • Integration into Enterprise Software: Just as AI has become an integral part of enterprise software today, GenAI will follow suit. In the coming year, we can expect to see established software companies integrating GenAI capabilities into their products. “It will become more common for companies to use generative AI capabilities like Microsoft Dynamics Copilot, Einstein GPT from Salesforce or, GenAI capabilities from ServiceNow or other capabilities that will become natural in how they do things.”
  • Intelligence as core to enterprise architecture: Paul believes “embedding intelligence as a core component of the enterprise architecture” isone of the most significant changes businesses will experience since the internet. Accenture now calls this the “modern digital core, which businesses must develop so that they can integrate new capabilities like GenAI, operate more effectively and set the stage for new growth..”
  • The Inevitable Backlash: With great innovation comes a (healthy) dose of skepticism and backlash. GenAI will face its share of challenges, including managing expectations. Over the next year, some may be disappointed when they “realize that generative AI doesn’t solve every problem as easily as they thought.” Paul cautions that careful consideration of the business case, costs, and scalability will be essential for a successful transition – “We’re encouraging companies to start even at the experimentation stage with a business case-driven view.”

We’re at the tipping point of one of the most significant enterprise shifts ever, and there is much more to come (that perhaps we are yet to fathom). As Paul put it, “I believe we haven’t seen some of the significant innovations yet from an enterprise tech perspective where it’s entrancing to watch AI ecosystem players that are innovating in the models themselves.”

Responsible AI isn’t just a push from the Tech community anymore, it’s a market-driven requirement.

As organizations gear up to integrate GenAI into their operations, Responsible AI has moved from a push from the tech community to a market-driven requirement. In our discussion, Paul noted that while the foundations of fairness and ethical AI have remained consistent over the last few years – the approach has shifted. In the past, efforts were focused on pushing to educate people about these concerns; however, today, “what’s different now is that there’s a pull to find information on responsible AI because they understand the importance…and heightened risks of GenAI”.

With the escalating risks concerning intellectual property and the emerging concerns related to misinformation at scale (including the potential creation of GenAI-generated deep fakes) – a set of unique challenges has arisen with GenAI. These challenges have been instrumental in driving the demand for Responsible AI. Paul stressed the urgency for organizations to promptly establish a systemic foundation for responsible AI practices.

Bottom line: We’re at the tipping point of one of the most significant enterprise tech shifts ever. The first movers are the ones that will have an advantage…

No one is immune from the impacts of GenAI, and conversely, everyone has an opportunity. “What will make a difference is that the first movers will have an advantage. Those who now understand the technology and models, and look critically at their data estate, will establish a solid digital foundation and will have a sustainable competitive advantage.”

There you have it, folks. It’s a brave new world; are you ready to seize it?

Posted in : Artificial Intelligence, GenAI, Generative Enterprise


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