Transformation in a Time of Uncertainty
June 20, 2023 | San Francisco
The Bloomberg Intelligent Automation Roadshow was on the West Coast to explore ways in which organizations can not only offset economic pressures but thrive by implementing intelligent automation systems that offer a return on investment.
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- Alissa “Dr. Jay” Abdullah, Deputy Chief Security Officer & Senior Vice President, Mastercard
- Joanne Chadwick, Chief Information Officer, Digital Transformation, Santander Bank
- Zulfi Jeevanjee, Executive Vice President & Chief Information Officer, Allstate
- Bill Lobig, Vice President, Product Management, IBM Automation
- Francesco Sartini, Chief Operation Officer, BlueIT S.p.a Societa Benefit
- Cynthia Stoddard, Senior Vice President & Chief Information Officer, Adobe
- Dominic Titcombe, Executive Vice President & Chief Information and Product Officer, Delta Dental of California
- Joe Vaughan, Chief Technology Officer, MoneyGram
- Rachel Metz, AI & Technology Reporter, Bloomberg
- Mark Miller, Global Editor, Bloomberg Live Experiences
IBM is currently moving from addressing pandemic-driven fragilities to focusing on productivity and efficiencies, said Bill Lobig, Vice President, Product Management, IBM Automation, setting a positive tone. It’s also about getting past workforce disruptions and helping people be more successful in their careers. When it comes to generative AI, the future of business lies in “changing inputs to get even more output.” IBM is using conversational AI to help people be more effective. Despite the fears around it, “We should all keep in mind that machine learning and AI, no matter how sophisticated it is, [is] only as good as the data it’s trained on, and that data came from people, or systems or sensors that were created by people. That tells me that generative AI cannot produce unique or original thought.”
Panel Discussion: Automation that Packs a Punch
Joanne Chadwick, Chief Information Officer, Digital Transformation, Santander Bank said that automation for the bank means looking for end-to-end process changes, “from the customer journey all the way through to the back office operations, making sure that we fully understand the happy paths and also the unhappy paths, and pulling in all the different stakeholders, like AML, fraud and legal.” On the extent of automation, she said their North Star is zero back office, but that’s not currently realistic.
Asked about a good automation idea that didn’t work, Joe Vaughan, Chief Technology Officer, MoneyGram recalled a time when the organization was adopting Robotic Process Automation. A treasury function required daily, intense human spreadsheet data work. “We pointed the bot at that problem, watched it for about a month and said, ‘Oh, this is great!’, then we turned our back on it, and our vendor changed the website. So, suddenly, the bot broke. It was not a great day to be in treasury or IT.” It reinforced the premise that automation is a discipline and a culture that requires monitoring.
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His firm helps companies digitally transform while remaining profitable. With that in mind, Francesco Sartini, Chief Innovation Officer, BlueIT S.p.a Societa Benefit, said, “We are not sure we can change the world with the reduction of the IT environment.” Not when customers are looking for more, like additional data centers and other resources. “But what we can do is reduce in an efficient way the number of resources used by our infrastructures.” He spoke about using IBM’s Turbonomic software for an intense view of customers’ IT environments, from the application to the infrastructure layer.
Case Study: Fostering a Culture Open to Change
Cynthia Stoddard, Senior Vice President & Chief Information Officer, Adobe described experimenting with hybrid work and collaboration well before the pandemic through “Lab82,” a program dedicated to testing new workplace experiences, named in honor of the company’s founding year. She credits that culture with fostering an agile team that still surprises her with efficiency. When the pandemic hit, one of their challenges was onboarding more than 1,000 interns just three months later. The typical solution would have required consultants and many more months of work. Instead, an internal team figured out a secure way forward in just a few weeks. “The pandemic helped people work in a different way so that they could be innovative and creative without the long, drawn-out steps we would do in the past.”
Panel Discussion: Automation and ROI
Alissa “Dr. Jay” Abdullah, Deputy Chief Security Officer & Senior Vice President, Mastercard was adamant about a strategy of fighting cyber criminals with the same tools they use. “AI opens up opportunities for the adversary, but on the flip side of that, it opens up opportunity for cybersecurity professionals, because now we’re just as ahead as anyone else.” It becomes about taking existing cybersecurity measures and “putting them on steroids,” and using ChatGPT to skip ahead to a security plan. “It’s the roadmap, not the solution. That’s how generative AI should be used.”
Zulfi Jeevanjee, Executive Vice President & Chief Information Officer, Allstate said ROI comes with working differently and making simple changes. Allstate is offering completely new products and customer experiences, with a target of one-third of the U.S. this year. “A few months ago, we rolled out a new product, we didn’t like what we saw, and the team was able to change it in a couple of weeks. We went from basically no one buying the product to almost our entire customer base picking it.” The solution was simple; change the experience to simpler, more engaging shopping.
Dominic Titcombe, Executive Vice President & Chief Information and Product Officer, Delta Dental of California noted they are not using generative AI right now, but recognize “a ton of opportunity.” Their current approach to complex tasks, like claims adjudication, is to “throw a lot of people at the phones.” He believes their best opportunity for automation is around intelligent contact center support. With a large data set as a foundation, he’s excited about training large language models to use their desktop procedures, “and create that super agent that our internal agents can rely on.”
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