New AI predictions were recently presented at IBM Think 2019. For more information, read the article below that highlights some key takeaways about the rise of AI and digital humans in financial services.
“AI is not going to replace managers, but managers who use AI will replace the managers who do not,” Rob Thomas, IBM General Manager of Data and AI predicted at IBM Think 2019. Every type of work is undergoing a transformation. A 16 trillion dollar opportunity, artificial intelligence will fundamentally change every business process, every role, and how organizations will impact their industries. AI implementation grew by 270% in the past four years, and 37% in just the past year, according to a 2019 Gartner study. Gartner credits this to the “maturation” of AI capabilities and how rapidly AI has become an “integral part” of digital strategies.
Digitally reinventing themselves, financial services firms are leveraging AI to achieve superior customer experiences, create new revenue streams and lower costs. With AI capabilities, digital humans or digital workers are now ubiquitous. They permeated sessions at Think 2019. To name a few examples just in the sessions I attended:
- IBM Project Debater
- Conversational systems by Geico and Hyundai
- Credit Mutuel’s virtual assistant
- Digital humans by UBS and UBank
- Banco do Brasil’s chatbots
- Aetna’s guided personal service
- Roman, IBM’s digital worker
- Behr’s conversational marketing
- RBS conversational agents
The following are my key takeaways on the rise of AI and digital humans in financial services and beyond to the impact on our broader society.
1. The future is already here
AI systems and digital humans are not the stuff of the future. They are already here. And they provide tremendous competitive advantage for companies who adopt them. Organizations and individuals should plan ahead—considering how they will transform their companies and themselves to take advantage of the opportunity before them.
IBM General Manager of Business Automation Gene Chao shared that companies must change how they conduct business and source talent to embrace AI for competitive advantage quickly. Business leaders must know how to manage a mixed workforce of digital and human labor, invest in new AI-related roles and training, and hire employees who know how to identify use case patterns and infuse industry and process knowledge into machines. They must hire employees who can become “bot masters.”
I would add that design thinking skills are also important. One of the interesting recurring themes around AI at Think was that companies should not simply apply AI to their existing processes and user experience, but consider the new opportunities and advantages AI can bring to reinventing legacy user experiences and services.
2. Free the humans!
According to Chao, intelligent automation can help reduce operational expenditure by an average of 2.63% and up to 7%, while increasing annual revenue growth by an average of 2.93 and up to 10% in a typical $1 billion company.
Of course, it is important to consider the psychological impact on humans and their trust in AI. Automation often seeks to eliminate tasks for human beings, and employees fear the loss of their jobs and livelihood. IBM’s approach to AI is not to replace humans, but rather to create augmented intelligence that helps amplify human cognition. Companies should ask: How do you leverage technology to help humans do what they do better? And how can technology bring value in such a way that it allows them to do higher value things?
On an interesting note: When Think 2019 attendees were asked to participate in the IBM Automation Manifesto, most expressed the desire for greater freedom to pursue personal pursuits such as spending more time with family, learning a new hobby or language, playing sports, traveling the world, and catching up on sleep. Ah, one can dream.
3. Logos, pathos, and ethos make a more perfect union
While logos is the inherent strength of AI-based systems, ethos and pathos are important in building human connection. I was pleasantly surprised to see IBM Project Debater use humility to build an ethos or type of credibility with the audience and both empathy and humor to develop pathos when arguing we should subsidize preschool.
Several companies expressed the need to develop a personality or tone for their brand through digital humans. Emphasizing the importance of developing an emotional connection with their clients, UBS and UBank explained that digital humans allow them to combine the best customer experience influencers from both man and machine, embodying an organization’s brand and creating significant value through emotional connection, personalization and consistency. Interestingly, they reported that their senior population particularly expressed satisfaction with the digital human experiences.
4. Bias is inherent in design
Circling back to logos: Since AI systems harness large amounts of facts and data, we might assume that they, therefore, present rational, logic-based, neutral and objective insights and decisions or recommendations. However, a common AI theme is the need to be aware of and monitor bias. Bias can be in AI models and data sets, yes; and good AI systems and practices provide lifecycle capabilities to reduce bias and restore trust. But bias is also in AI design itself—and the assumptions of what is included, valid and valued. As of today, 87% of the machine learning workforce is male. Inclusivity, data privacy, and gender identity, for example, are issues that require careful and thoughtful consideration when building AI systems to be fair, uphold human rights and reflect societal norms.
5. AI is not magic, but is the new electricity
While AI often feels surreal and the stuff of superheroes, at times, it is not magic. But it is like the “new electricity,” Rob Thomas says. It has the ability to transform every aspect of our professional and personal lives. AI is helping companies make better predictions, automate things they don’t want to do, and optimize their businesses. Simply put, AI is is the merger of automation with intelligence. AI automates tasks, routines, decisions, and workflows with rules-based process engines and inference technology. It does not occur with the snap of a finger.
IBM CEO Ginni Rometty discussed three types of AI that IBM Research teams are focused on during her Think 2019 keynote:
- Core AI—unifying learning and reasoning like Project Debater
- Trusted AI—lifecycle AI, including processes for the elimination of bias
- Scale AI—AI to automate AI
Rometty explained, AI should start outside in—focused foremost on the user experience—but also inside out as new workflows and data force companies to change and modernize their core applications and architectures with platform-driven services. “You need a platform to connect those two things—fueled by data and AI infused in your workflow,” she stated. She further noted that companies spend 80% of their time getting their data ready: “You will never have AI without IA, information architecture.” Rometty’s final point was that AI is the backbone of everything in the new digital transformation era and requires a robust cloud strategy to scale across the internet of things. Underpinning it all is the growing importance of trust, both in technologies and in their impact on the world.
And with that, she announced Watson Anywhere—the most open and scalable AI for business—can now be run in any environment–on premises, or on any private, public or hybrid-multicloud–enabling businesses to apply AI to data wherever it is hosted. Businesses will be able to infuse AI into their apps, regardless of where they reside. She also announced IBM Business Automation Intelligence with Watson, which helps build digital automation agents that will automate styles of work from mundane clerical tasks to complex knowledge work and include built in business controls to trust the agents with mission critical work.