Hannah Calhoon, vice president of AI for Indeed, uses artificial intelligence “to make existing tasks faster, easier, higher quality and more effective.”
She points to a recent initiative in which the job matching and hiring platform company started using large language models (LLMs) to add a highly customized sentence or two to the emails it sends to job seekers about open positions that match their qualifications.
The results have been significant, particularly when considering that Indeed sends about 20 million such emails a day. Calhoon says that personalization has yielded a 20% increase in the number of candidates applying for those positions and a 13% increase in successfully landing the job.
“So one tiny little sentence is better for job seekers and employers,” she says.
Like many organizations, Indeed has been using AI — and more specifically, conventional machine learning models — for more than a decade to bring improvements to a host of processes. But Calhoon said the company in the past few years has been using AI to transform its products, services, and workplace. And she expects AI to drive even more impressive innovations as both the technology and the enterprise’s ability to use it mature.
“AI changes the bundle of tasks that are in a job, and AI over time will change the nature of roles. So jobs will look much different than what they are today. That’s where we think the world is going,” she says.
Consequently, workers won’t see incremental bumps in productivity; rather, they’ll experience multifold gains in productivity. They’ll be able to perform tasks, such as computer coding, that they currently cannot do without specialized training, and they’d be able to do so at a level and speed that exceeds what the experts can do today. And they’ll have the time and ability to use AI to innovate in new ways, because AI will handle more of the mundane tasks that now take up their time.
“AI will let us automate away a lot of the toil that people don’t like and create more moments and space for human connections, problem-solving, and collaboration,” Calhoon predicts. “There is an opportunity to use AI to make work better, certainly at Indeed but also for millions of people around the world. That is transformational.”
Transforming into ‘highly automated and efficient operations’
It’s no secret that AI is top of mind for CIOs and their organizations.
In fact, IT’s embrace of AI is nearly ubiquitous, with 89% of IT decision-makers surveyed for Foundry’s 2024 CIO Tech Priorities study saying they’re researching, piloting, or currently using AI-enabled technologies — up from 72% in 2023.
Moreover, 64% of those IT decision-makers expect AI and machine learning to significantly alter the way their business operates over the next three to five years, up from 39% who said the same in 2023.
More specifically, IT leaders believe AI will transform their organizations primarily through process automation and efficiency gains, as well as enhanced customer experiences.
CIO.com / Foundry
They also cited AI/ML capabilities in specific areas — such as risk management, fraud detection, smart manufacturing, predictive maintenance, quality control, and personalized employee engagement — as fueling transformation.
And they called out natural language processing (NLP), a subfield of artificial intelligence, as a specific driver of transformation.
“The interest in AI that began last year has turned into frenzy as organizations grow even more convinced of its potential to automate everything from business processes and decision-making to software development to creating written content,” Foundry writes in its 2024 CIO Tech Priorities report. “Now, a majority of organizations will invest in AI technologies this year to transform their businesses into highly automated and efficient operations.”
Scale, scope, and depth
Moe Asgharnia, CIO of BPM, which provides assurance, advisory, tax, and wealth management services, can attest to the transformative power of AI.
He says his firm in early 2024 launched a custom-built AI tool that enables employees to quickly research tax laws and tax scenarios. The AI sifts through vast amounts of dense information to yield insights in seconds, and it puts that power in the hands of workers throughout the organization, not just senior-level employees or seasoned analysts.
“That has enhanced our response times and really supported better resource utilization across the firm,” he says.
Of course, CIOs could credit many technologies over the decades — from the first personal computers to robotic process automation — for producing results such as improved speed and optimization.
AI, however, does it at unprecedented levels in terms of scale, scope, and depth, Asgharnia says.
Asgharnia and his team built the tool and host it in-house to ensure a high level of data privacy and security. They used OpenAI as a back end and its API to push and pull data. And they used a web interface to create a user-friendly experience so that the “look and feel is very similar to what our colleagues expect from ChatGPT, so they’d find it simple to use.”
The instance was trained on US federal tax publications and continues to train on additional tax resources so that it will produce even more insights for firm employees, Asgharnia says.
“It allows us to analyze all possible paths to determine what’s in the best interest of our clients, and it can do that in seconds. We can develop unique responses relevant to each scenario we’re trying to address. In the past that work would mean sitting with partners, doing research, setting up calls, [all of which] would take significantly more time,” he says.
“Now staff has a higher sense of autonomy and a higher sense of trust in the decisions that they are making using this research platform because they know it’s backed by valid data from the IRS and other reputable tax resources. That translates into better research, better service for our clients, and better response times.”
He adds: “I’d classify that as transformative because traditionally accounting firms have had a cut-and-dry process for escalating questions for complex tax decisions. This cuts it down quite a bit. And it allows associates to focus more on complex issues versus basic tasks.”
Asgharnia is now building on that success, expanding the tool to other areas and geographic regions, starting with Australia and that country’s tax laws. He expects that this expansion of the tool will transform in similar ways how the firm operates in other functional areas and in other countries, too.
Sanjeev Kumar, vice president and chief data and analytics officer at Gainwell Technologies, a provider of healthcare technology services for state governments, also has seen the power of AI in his company.
“There are applications of AI that are incremental but there are others where it is transformational,” he says.
Kumar cites the use of AI for performing documentation as an illustrative example, as the intelligence ultimately saves “weeks or months” of human time “freeing them up to do more important tasks,” making people not only more productive but increasing the quality of work performed, too.
“There are applications that are changing how people work; AI is changing 50% to 60% of what they do,” he adds.
He describes how AI is transforming his company’s work: “As we build and evolve our population health management models at Gainwell, AI is a core element of our roadmap. Its transformative potential lies in better identifying individuals and populations who are most at risk of developing chronic conditions and informing more effective treatment programs for them. Incremental — or additive — value is gained by applying AI modeling to help identify the onset of other diseases like COVID-19 and predicting the likelihood of members developing other diseases or geographic regions that might be particularly impacted.”
‘Solving problems that weren’t solvable’
Other enterprise leaders report similar gains with their AI initiatives.
The AI Pulse Survey released by professional services firm EY in July 2024 surveyed 500 US senior leaders across industries about their AI initiatives and found that 77% of those whose organizations are investing in AI say they’re experiencing a positive ROI on operational efficiencies, 74% report a positive ROI on employee productivity, and 72% say as much regarding customer satisfaction.
Such statistics don’t tell the whole story, though, says Beatriz Sanz Sáiz, EY’s global consulting data and AI leader.
Like others, Sanz Sáiz sees AI delivering benefits in productivity, efficiency, experience, safety, automation, and many other areas that are so significant in scale and scope that they’re transformational.
She also sees AI transforming how work happens — an area that yields particularly disruptive results.
“We’re seeing lots of efficiencies where back, middle, and front-end workflows are being automated. So, yes, you can automate your existing processes, and that’s good and you can get a 20% [improvement in efficiency]. But the real gain is to reimagine the process itself,” she says.
In fact, the gains AI can bring when used to reimagine processes is so significant that she says AI challenges the very concept of “process” itself. That’s because organizations can use AI to devise ways to reach specific desired outcomes without having a bias toward keeping and improving existing workflows.
“Say you want to increase customer satisfaction by 35%. That’s the input. It’s less about how the process works. The process itself becomes almost irrelevant,” she explains. “The technology is good at achieving an object, a goal, and the concept of process itself, the sequence itself, is blown away. That is conceptually a big shift when you think of the enterprise, which is built on three things: people, process, and technology, and here’s a technology — AI — that doesn’t care about a process but is instead focused on outcome. That is truly disruptive.”
Agustin Huerta, senior vice president of digital innovation for North America at IT services company Globant, says he, too, sees a growing number of use cases where AI is disrupting conventional processes, expectations, and ways of work.
Some have been around for a while, he says. He cites use of AI for fraud detection as case in point, noting how the technology, with its ability to instantaneously analyze data for patterns to detect anomalies, has been used for years to deliver big returns for financial firms and their customers.
Now, thanks in particular to generative AI and its ability to understand and analyze not only structured but also unstructured data, organizations are applying AI to an increasing number of truly disruptive use cases.
“Everyone is looking at AI to optimize and gain efficiencies, for sure. And they’re now using AI in areas that previously were seen as not being able to be optimized,” he says.
His own company is one example. Globant used gen AI to create an advanced search tool for its media industry clients. This Advanced Video Search enables users to find a specific moment in their video content libraries in seconds by using text or image-based search; users can, for example, search via a specific audio line or a text description of an action happening in the video.
Such AI use cases show how the technology is not merely delivering a productivity gain; instead, it is handling a volume of work at a scale that would be impossible for humans to feasibly do — or do within any degree of reasonable time or cost, says Ed Watal, founder and CEO of Intellibus, an IT strategy consultancy and platform engineering firm, and an adjunct assistant professor for AI at New York University.
The pharmaceutical industry’s use of AI for drug discovery, the healthcare sector’s use of AI for precision medicine tailored to the individual patient, and operations executives use of the technology to optimize supply chains to reduce costs and boost sustainability all demonstrate the transformations happening.
“We’re solving problems that weren’t solvable before,” he adds.
Not all organizations, however, are able to use AI to that degree at this time, Watal and other experts say. Many organizations don’t have the required data infrastructure, skilled technologists, or AI-ready culture to envision, develop, and adopt AI in ways that disrupt the status quo.
As a result, Watal says “a lot of what we’re seeing is still incremental in nature. But we’ll see more transformation in the future as we get AI governance right.”
