Putting Generative AI To Work Inside The Enterprise

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Over the last two years, we’ve seen AI evolve from science fiction and speculation into an everyday tool, swiftly transforming the business world.

Today, AI – and generative AI specifically – is integral to many aspects of enterprise operations. It’s routinely being used to streamline and automate processes across finance, marketing, production and HR, driving efficiency and creating new opportunities.

IBM pioneered mainframe computing in the last century and cloud computing in this one. Most recently, it has reinvented itself as an enabler of enterprise AI innovation. Today, it uses the term “digital labor ” to identify tasks and processes that are prime for automation.

The key message is that by applying the latest in generative AI language models and predictive business intelligence, organizations can become smarter, faster and more efficient.

Additionally, by automating the routine “busy work” that conventionally takes up too much time, professionals can spend more time on the strategic, high-value tasks that drive real growth.

A perfect example of this is seen with one of IBM’s most exciting sporting customers, the world-renowned, Sevilla FC .

While crowds are drawn to the action on the pitch, behind the scenes, a team of technologists and business professionals ensure the club is supported by a well-oiled and efficient machine. In this respect, AI is increasingly the star striker.

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How Sevilla FC Uses Generative AI For Talent Scouting

Seven-time Europa League champions, Sevilla FC is a football club with a strong pedigree on the pitch, but also when it comes to leveraging technology. Its generative AI strategy is the latest element of this.

The club’s expertise at scouting for new players has always been a key factor in this, Chief Data Officer of Sevilla FC, Elias Zamora Sillero tells me. And now this process is being enhanced and automated with the help of IBM’s generative AI technology.

“We’ve reached a pretty high state of maturity in the organization in terms of the way we can perfectly identify talent based on numbers and performances. But we wanted to also identify talent in terms of expert human opinion.”

To do this, it applied natural language tools to its database of nearly one million reports created by professional football scouts over the club’s 130-year history.

"This is a huge source of information but they are not numbers. They can include things that have nothing to do with numbers; for example, it’s very difficult to [quantify in numbers] leadership … or how the other players believe in you.”

“This kind of thing is difficult to be measured by technology, but it's easily understood by humans.”

“The result is a tool that allows the club’s scouts to simply write a description of the kind of player they are looking for. An example might be a “strong center-forward that can really contain the defense and is good with their head.”

It then provides results based on combining numerical performance data with qualitative human insights.

This has given the club the ability to identify talent with a higher degree of precision. “The generative AI works for us in unlocking the full potential of human knowledge,” Sillero tells me.

Generative AI has proven so transformational at the club that Sevilla FC now plans to commercialize its AI and data solutions by providing consultancy services to other clubs.

“Our idea is to work together with IBM to make Sevilla FC not just a football team, but a consultant in terms of data strategy in football or in sport in general,” says Zamora.

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Digital Labor

The term digital labor refers to the use of AI-powered tools to automate and streamline many business processes, leaving employees free to focus on higher-value tasks.

As we saw with Sevilla FC , HR is a great example. But it isn’t only useful for organizations searching for the next football superstar. AI is quickly becoming the go-to method for internal communications, answering employee questions, scheduling interviews, reviews and appraisals, engaging in talent acquisition, and drafting everything from guides, handbooks and job descriptions.

As IBM’s VP for Product Management and Digital Labor Software, Parul Mishra, tells me, “Now every employee at IBM goes to this one place and is able to ask any question related to HR ?– ?it could be as simple as how many vacation days do I have left, or what is the policy for hiring in a different country? Or it could be an automation task like I have an employee that I would like to move to a different department.”

“Typically, for these kind of tasks, people would have to [go through] 20 to 30 steps just to do that. Now, the natural language is responsive … it’s a very guided experience,” Mishra says.

Beyond HR, digital labor creates efficiencies across many other areas of business operations.

“We have procurement use cases, finance use cases, cash collection and invoicing, so really a backend business process where there are multiple systems and a lot of manual data back and forth is ripe for this kind of technology.”

To facilitate this, IBM builds tools that it calls assistants – specialized AI helpers designed to be experts at carrying out specific tasks. It has also recently unveiled a new platform called watsonx Orchestrate to streamline the process of creating these assistants and putting them to work.

Mishra says “Within minutes a knowledge worker can come and configure an assistant that’s able to perform tsks on their behalf, logging into systems and getting data.”

“This is a power that’s shifting from a lot of heavy-handed technical experts to knowledge workers … the more power we give our employees to make their own jobs productive, the better off they are.”

By combining automation with generative AI, Mishra suggests that employees can be freed from the “drudgery of work” and spend time on more valuable, rewarding assignments.

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The Future Of Generative AI In Enterprise

As AI inevitably grows more powerful, and generative AI becomes more capable, there’s no doubt we will see an even more transformational impact.

“The AI assistant technology will become so sophisticated in the next couple of years, it won’t just be models; it will be agents … handling multiple things. Breaking down very sophisticated natural language requests into pieces and routing it to the right spot,” Mishra tells me.

Through this "agentic framework," generative AI tools will evolve from simply answering questions to autonomously performing complex, multiple-step tasks in a way that integrates seamlessly into our daily workflows.

This will enable businesses to become faster and more agile at making the data-driven decisions that impact on the experience of customers as well as their own workforces.

Of course there will be challenges around data quality, cybersecurity, bias and privacy. However, these will push every organization to learn how to use AI in a responsible, transparent and safe way, and develop a culture of ethical AI use.

As businesses continue to explore and adopt these technologies, progressing more projects from pilot to full-scale deployments, the rewards will include new opportunities for growth and innovation and increased competitive advantage.

To learn more about digital labor, click here and watch the full interviews with Sevilla FC here , as well as with Parul Mishra here . IBM watsonx Orchestrate is the platform for enterprises who are creating and deploying purpose-built AI assistants for any use case across any domain. Learn more about watsonx Orchestrate: https://ibm.biz/BdmuJr

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About Bernard Marr

Bernard Marr is a world-renowned futurist, influencer and thought leader in the fields of business and technology, with a passion for using technology for the good of humanity. He is a best-selling author of over 20 books , writes a regular column for Forbes and advises and coaches many of the world’s best-known organisations.

He has a combined following of 4 million people across his social media channels and newsletters and was ranked by LinkedIn as one of the top 5 business influencers in the world. Bernard’s latest book is ‘Generative AI in Practice ’.