A recent report from Accenture found a striking dichotomy. Seventy-five percent of surveyed executives believe they risk going out of business in five years if they don’t scale AI. Yet despite this critical perceived need, 76 percent say they are struggling to widely adopt AI in their businesses.
Why the disconnect?
AI may be the phrase on everyone’s lips, but so far, it’s been more hype than substance. In 2020, that starts to change. As AI gets smarter, 2020 will be the year we reckon with the consequences, discuss the need for regulation, and move toward more powerful applications of AI than virtual assistance and product recommendations. The conversation will move beyond shiny objects, hollow hype, and shaky vendor promises – and become more nuanced, balanced, and tangible.
Here’s what I predict will drive the AI conversation next year:
The industrial revolution began with using machines to perform mundane, cumbersome and repetitive tasks. In these early days of the AI revolution, it’s largely been the same. Companies aren’t using AI to entirely disrupt their businesses or radically transform customer experiences as much as they’re using it to create efficiencies and save employee time. But we’re about to cross that chasm.
In 2020, we will finally see the fruits of millions of hours of engineering effort. As a result of more data and more maturity, AI systems will actually be able to learn and act on their own, and therefore show much greater value. AI will become the bedrock of the enterprise, acting as the key component of enterprise orchestration and optimization, providing a level of network assurance unattainable with previous tools. With AI, the network will literally be able to run and optimize itself.
Beyond IT, AI will add levels of intelligence that grant enterprises a newfound freedom to connect with customers, employees, students, and patients in new and meaningful ways. What used to be seen as just a tool to manage the network will expand its capability to allow almost any corporate entity to garner knowledge they never knew the network could provide. Healthcare practitioners will use AI to monitor whether pills have been distributed to a patient, retailers will be able to see which part of the store a customer is in and send location-based offerings, and educators will be able to create connected classrooms and deliver personalized learning solutions for each student.
Those wary of AI and automation often warn about technology taking jobs away. The sentiment behind those fears is valid, but the argument is over-simplified. AI won’t eliminate the need for human intelligence and judgement. The success of any bold digital transformation initiative entirely depends on the strength and intellect of the people within the walls of enterprises. But AI will change what employees do on a day-to-day basis and drive them to learn new skills. This is par for the course — businesses and employees have been evolving alongside major technological advancements for decades, from the industrial revolution to our internet-driven economy today.
Though some companies may choose to recruit new full-time employees with specialized experience, in 2020 I expect more companies to focus on upskilling their existing workforce and teaching teams how to use new software, automation, and analytics tools. Not only will that training expand employees’ capabilities and encourage professional development (which helps with retention and recruitment), it empowers your workforce to be more proactive and makes them more effective at ensuring legacy technology and new AI technology fit together.
For Boeing, 2019 was marked by a second tragic plane crash, the grounding of its 737 Max, and questions regarding the role the plane’s automated system played in the crash. Why did the pilots not have the ability to override the plane’s self-driving capabilities?
In this era of self-driving cars and autonomous systems, the Boeing incident made us pause and reflect on our technology-enabled world. In 2020, this reckoning will continue. The introduction of autonomous cars has raised ethical and philosophical questions, such as The Trolley Problem. Should a self-driving car be programmed to protect the driver at all costs, or to do the least amount of damage within the overall society? Should a car be programmed to break the law by driving onto a curb to avoid a child on the road? These types of questions need to be considered in the creation and adoption of new technologies.
As enterprises adopt artificial intelligence technologies, similar considerations are called for. Creating an ethical AI is essential. The infamous Amazon recruitment ML engine, abandoned in 2017 due to its bias against women is an example of what can go wrong when ML and AI tools are trained on biased data. The project was designed to make the time-intensive task of hiring easier, but it ended up illustrating the potential pitfalls of relying on algorithms over human judgement. Careful consideration for where, when and how new technologies are adopted is essential. And the time for this discussion is now – before immature technology is brought to market or more accidents occur.
Across every industry, CIOs will tell you AI is a critical element to their business’ growth. We can all recite the potential benefits, we’ve all read the headlines. But 2020 will be the year AI moves beyond talk, and breaks through in a more meaningful way. And it’s going to be the organizations that prioritize planning, infrastructure, and data that will rise to the top.
This blog was originally published on VMBlog on January 17, 2020.
