AI and the Future of Business
Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of them.
COVID-19 disruption has left enterprises with no choice but to reassess digital transformation investments and roadmaps. While less important projects are delayed, transformation projects involving AI and automation are receiving a lot of attention right now. In just the last 60 days, the adoption of varying levels of AI technologies across the enterprise surged with an incredible sense of urgency. One area where AI can make a tremendous impact — yet one we’re not really talking about it — is modeling future scenarios based on myriads of new data stemming from pandemic disruption. Beyond automation, adding an AI Futurist as a virtual strategic advisor to the C-Suite can help executives navigate this Novel Economy as it takes shape over the next 36 months. In a time when no playbook, expertise, or best practices exist, perhaps this is AI’s moment to shine. AI in the Enterprise is an Essential ItemAlmost overnight, organizations were forced to hyperfocus on critical priorities and accelerate their digital transformation from legacy, analog-first models to digitally native systems, workflows, and processes. Many organizations weren’t fully prepared for such a disruptive and swift response, however, pushing stakeholders to narrow their focus toward pressing issues and burning platforms. Among cloud and cybersecurity investments, the adoption of artificial intelligence in various forms is also soaring. Forrester predicts that the COVID-19 crisis will only further accelerate enterprise automation as it becomes a boardroom imperative. Investments in AI-powered applications can help place organizations on a more advanced path toward future disruption-proofing and overall competitiveness, now. AI, machine learning, and automation are each — in their own way — fast-tracking transformation to scale critical areas of demand and capacity where humans can’t. These instances include: automating repetitive operational workflows; engaging increased volumes of customers in digital service channels; organizing and interpreting data to improve human decision-making in critical business areas; and understanding evolving behavioral patterns to optimize for new standards in customer engagement and e-commerce.
AI adoption is also accelerating across manufacturing, logistics, pricing/inventory management, and supply chains. Whether it’s robotic process automation (RPA), conversational AI, real-time and predictive analytics, or deep learning black or glass box modeling, AI is helping organizations ensure business continuity, stabilize against disruption, optimize processes, flow, and performance, and more accurately predict demand and opportunities. Additionally, AI can mitigate risk and promote business resilience beyond continuity to survive and thrive against today’s unknowns. Prioritizing the Intelligence in AIIn February 2020, I visited Mumbai to speak at the NASSCOM Technology and Leadership Forum on the “State and Future of Quantum Computing” in the enterprise. At the time, COVID-19 was spreading around the world.
In my talk, I concluded that even though quantum computing capacities could be feasible in ten years, enterprises needed to form — now — a center of excellence to start understanding, experimenting with, and participating in useful quantum-related forums. The idea isn’t to jump on the next buzzwagon, but instead, build necessary expertise now and develop iterative roadmaps as quantum computing evolves. This would help organizations evolve — through experience, expertise, and strategic partnerships — to keep up with or stay ahead of what’s next. The same is true for artificial intelligence, especially in an era of COVID-19 disruption. Following my presentation, I was asked about quantum computing’s potential to quickly find a vaccine should those capabilities exist today. While ultimately possible, I emphasized the importance of today’s AI capabilities to hyper-focus on such tasks. We have incredible supercomputing technology available today that we’re not using to its full potential in the enterprise. We need to escalate strategic AI roles to the C-Suite to navigate the many unknowns we face. Like with quantum computing, organizations would strategically benefit from establishing a center of excellence or “office of innovation” around artificial intelligence to advise CxOs (and boards) to survive and thrive in this Novel Economy. Who’s Defining the New Normal? Meet Generation-NWho’s leading your digital transformation? Is it the CEO, CFO, CIO, the board, customers, or…? Consistently, the answer is: COVID-19. Who’s leading the Digital Transformation of your company?Many of today’s AI implementations that make today’s tech headlines though are designed to optimize specific tasks in specific applications. For example, in marketing, AI is helping businesses identify engagement patterns and preferences to deliver more relevant messages, at the right time, on the right device, in the right context. But, let’s assume that most of the data we have pre-pandemic is outdated. It depicted a world that no longer exists. Who or what is gathering real-time data to not only market more effectively, but also understand how the world is changing and where it’s headed? You can’t understand the present or predict the future without data. At the same time, you can’t effectively guide an organization if you can’t identify with its stakeholders or customers. Even with post-COVID-19 data sets, data can’t think for you. To navigate these cliched, but still accurately described “uncertain times,” executives need access to extraordinary brainpower, both human and digital. Data is the fuel for innovation. But empathy is the source of relevance. Combined, data-driven empathy can accelerate transformation.
For instance, today’s evolving customer and employee, including you and me, can not be understood based on basic generational categorization, i.e. boomers, Gen-Xers, millennials, and centennials. Post pandemic, we’ve become part of a more inclusive and expansive group by nature of disruption. I call it Generation-Novel or Generation-N. Birthdates and demographics aside, we’ve collectively become part of Gen-N the moment COVID-19 took over the world and forced us to shelter in place, lockdown, and quarantine — and pushed us outside of our everyday norms, forcing us to think, behave, and feel differently…every day. Offices, stores, and events shut down. Remote working and schooling were suddenly the new standards. Millions of jobs were eliminated. Shopping, service, and most organizational engagement shifted online. Real-world shopping for essential items became competitive, surreal, and something straight out of The Hunger Games. Toilet paper, sanitizer, paper towels, wipes, bleach, webcams, were all suddenly more precious than precious metals. Combined, this incredible, sudden global disruption served as the genesis of a Novel Generation of consumerism and accordingly, a Novel Economy. Any data sets pre-pandemic, any “future of…” scenarios previously developed, and any roadmaps based on either, need a redux. Our Ctrl-Alt-Del moment started on Day Zero of COVID-19. Hiring an AI FuturistWhen we talk about the new or next normal, what does that mean? What does it look like? What are the scenarios we need to consider? What are the models we need to develop to best respond and even grow in this Novel Economy? Executives must immediately consider whether they have qualified and capable resources at the ready to make fast, informed decisions, beyond survival and business continuity to navigate market shifts and guide the mid-to-long-term health of the organization. Important questions to consider include: Who on staff is an expert in pandemic response? Who within the network of resources is a specialist on the psychological, emotional, and behavioral impact of global stress and anxiety and how that affects consumer (and employee) values, aspirations, and decision-making? Who is an authority on economic policy or market scenario planning? Who among us is experienced in studying human behavior, societies, and relations? While the promise of AI and its current reality in business has been long debated, new and unusual times demand inventive and innovative measures. There’s an awful lot of unknowns to consider at a time when every decision counts more than ever. We need new models, now, and without artificial intelligence, response times to the COVID-19 crises will be prolonged and inexact. I don’t know how many organizations have the luxury of human trial and error. A new approach is needed.
Custom deep learning tools are available now, not just in labs, but in business applications. For everyday organizations, specific AI solutions can be built upon neural networks and layers of nodes to process explicit data for desired outcomes at levels well beyond human capacity. Perhaps this is the ideal time to promote AI to the C-Suite with the creation of a new role, the AI Futurist. Buzzwords aside, this is a role that can benefit many organizations. It is not a futurist’s job to predict the future. Instead, futurist studies patterns and trends to understand and anticipate what could or should happen in future scenarios. Their work then helps decision-makers prepare for and gain an advantage ahead of those likely changes. By forecasting alternative or ideal futures, futurists can assist in the development of high impact strategy and investment decisions. The goal is to then plan and execute accordingly to affect the future and influence events and outcomes to drive current and possible scenarios. An AI futurist can accelerate the study of new data sets to serve as a digital advisor to executives around COVID-19-inspired scenarios. The idea isn’t to displace humans in this role. Instead, an AI Futurist would augment a specially created human task force consisting of scenario planners and economic, health, and tech experts to outline possible events and trends and to guide executives through these disruptive times. At Salesforce, the company where I work, Peter Schwartz serves in the capacity of resident futurist. Along with the team in the company’s “Office of Innovation,” Schwartz led the scenario planning and research initiatives behind the recently launched Work.com initiative to help businesses reopen safely during the current pandemic. The results are outlined in a playbook that describes four models of potential economic outcomes shaping the Novel Economy. They’re meant to guide executives as they ponder strategies for continuity and resilience: What decisions can I make now to ensure my business is resilient in the next normal?How can I make sure that I see the signs for change early enough, so I can act quickly when the time is right?In case of emergency: break glassAn AI Futurist could help executives consider possible future scenarios unique to their data sets and interests to more effectively navigate uncharted paths forward today. Specifically, algorithms can be developed to model how COVID-19 potentially affects markets, supply chains, productivity, sales, et al., to then focus considerations and investments for the best possible outcomes while mitigating risks. Of course, AI and data alone can’t make decisions. But, when partnered with human experts and relevant data, purpose-built AI could add a significant competitive advantage. By accelerating the capacity and value of bringing innovation into the business at every level. And since the CFO is now involved in all major spending decisions, models could be developed to demonstrate time to value and ROI negligible and even exponential against the investment. Installing an AI Futurist would need to be done with purpose and a comprehensive, real-time platform built upon the following:Market and economic dataSupply and demandSupply chainsUnbiased algorithms and mindsetsAI training, without bias and with full ethics integratedHuman counterparts who are well-versed in managing AI systemsData-driven empathy (the ability to humanize algorithms and resulting data when you cannot normally understand or relate to people, behaviors or resulting patterns)Human counterparts as part of a command center to translate insights into meaningful stories and actionable initiativesIt’s Not Science Fiction, It’s Science RealityFor years, strategy games have been a testing ground for artificial intelligence. In 1997, IBM’s Deep Blue became the first machine to beat a reigning world chess champion in Gary Kasparov. In 2011, IBM Watson defeated two human contestants, considered among the greatest to play the game. More recently, Alphabet’s DeepMind tackled StarCraft, considered one of the most challenging real-time strategy games, which earned consensus as a “grand challenge” for AI research. In all cases, however, AI is learning how to deliver value to businesses with many labs offering research consultancy opportunities to create custom applications. As such, purpose-built capability already exists for those ready for such partnerships. Perhaps prior to COVID-19, the sense of urgency wasn’t as critical. Now, companies need to move fast to get ahead of trailblazing competitors. Salesforce Research, for example, recently announced “AI Economist,” a purpose-built AI model to study how governments can optimize tax policies, productivity, and social equality for everyone. In a research paper outlining its two-level deep reinforcement learning approach, the AI Economist learned dynamic tax policies that created a model 16% more effective compared to an adaptation of the Saez tax formula, a prominent tax framework, US Federal income rates, and the free market, i.e. no taxes. It also improved equality by 47% compared to the free-market at only an 11% decrease in productivity.
Chief scientist and head of Salesforce Research Richard Socher leads a team of researchers that includes senior research scientist, Stephan Zheng, lead research scientist Nikhil Naik, and senior research scientist Alex Trott. This team partnered with David Parkes, a computer science professor running an economics and computer science research group at Harvard. Together, they developed a model to give economists and policy-makers intelligent tools to base their decisions on future economic policies that are more in line with how the world is evolving. By simulating millions of years of economies and exploring a variety of tax frameworks, the AI Economist can predict how people would respond to a tax, for instance, whether it will incentivize them to work less or more. “Currently, the AI Economist is solely focused on taxes,” explained Socher in an interview. “However, we think RL [reinforcement learning] is promising for economics and could potentially be applied to navigating the economic aftermath of COVID-19.” This idea could be applied to developing an AI Futurist role within organizations now. Socher continued, “Economic simulations can factor in human behavior by using real-world, human data. Together with our RL algorithms, this could lead to AI-designed economic policies that could help accelerate real-world economic recovery. We are already thinking of ways to approach this and encourage researchers thinking about this to reach out to us.” Even though levels of AI have been circulating the enterprise for several years, artificial intelligence deserves a place within the C-Suite, of all times, now. MIT Sloan In late 2019, the MIT SMR-BCG Artificial Intelligence Global Executive Study and Research Report found that 9 out of 10 respondents agree that AI represents a business opportunity for their company. Additionally, a growing number of business leaders viewed AI as both an opportunity and also a strategic risk if not adopted. “What if competitors, particularly unencumbered new entrants, figure out AI before we do?” executives wondered. The idea of hiring an AI Futurist and establishing an elite unit of specialized experts isn’t science fiction, it’s a reality rooted in science. We live in new and unusual times and as such, need new and unusual approaches to respond and move forward. AI is now, more than ever, an urgent issue to address and a virtual, but the urgent voice of direction. Sebastian DiGrande who heads up strategy, data and analytics, digital, and customer efforts, at Gap Inc. works closely with the chief financial officer on AI initiatives. DiGrande warned in a conversation with MIT Sloan and BCG that hesitance to employ AI in business is “an existential threat: If we do not change the way we operate, the tools we use, the degree of automation and AI that we leverage, the industry and the customer will move on without us.” The key is not to limit our understanding of AI as a solution for automation or a digital means to improve or optimize existing business processes. The opportunity, the sense of urgency, is to use the concept of an AI Futurist as a strategic partner in navigating the Novel Economy and to accelerate business continuity, recovery, and a drive to overall business strategy and outcomes from this point forward.