The technology press is agog with predictions about the role of machines and the amazing progress being made by learning algorithms. From home-vacuuming robots and self-driving cars to virtual support with chatbots, the increasing incidence of artificial intelligence (AI) is creating exciting new business and social paradigms.
The excitement, however, is accompanied by skeptics who believe this progress represents the dawn of a world where humans will become subservient to machines. Hollywood has also done its part with many movies portraying the harmful effects of AI.
Regardless of one’s own personal views on what role artificial intelligence should/will have, AI is already profoundly altering business and social spheres. Amidst all the hype, the real revolution is happening in incremental developments that touch all industries.
At its core, AI represents a set of algorithms that aim to replicate and surpass human reasoning, knowledge, planning, learning, natural language communications, perception and the ability to move and manipulate objects. The actual mathematics constitute (1) numerical observations of system behavior under many input conditions, (2) mathematical modeling of the behavior to a best-fit approximation and (3) predicting system behavior under new input conditions. These generic steps find applications in a variety of business, operational and social settings. Market opportunities are real, but the ultimate success or failure of any business hinges much more on the market readiness, productization and commercial savvy than it does on specific implementations of machine learning algorithms. Compelling technology is necessary, but it’s not enough to create a successful company. In other words, exceptional technology in the absence of a viable business is nothing more than a science project.
While AI and machine learning will certainly change how we interact and perform tasks, they will never eradicate the need for human intervention, inspection or innovation. The human vs. machine mind demonstrates significant differences when it comes to contextual decision making, emotion, and qualitative reasoning. AI should be seen as a supplement to business intelligence, not a substitute for it. This is especially the case in evaluating strategy and innovation. History is rife with successful businesses that were created under the shadow of extreme doubt and skepticism.
As I look back on 2016 and look ahead to 2017, I realize AI-related business topics will continue to rise to prominence. Mckinsey’s analysis of work activities in U.S. occupations, estimating that technical feasibility for automation exists in over 60-75 percent of tasks. While scary and disruptive, this represents a wake-up call for enterprises to adopt new AI-based strategies or risk being irrelevant. I wonder if the move toward AI will emulate the wave of business-process outsourcing that occurred in the early 2000s?
Firms that invest in automation and acquire the people/skills to harness AI will have a competitive advantage. Having a long-term view of the complete AI technology stack – hardware, connectivity, cloud infrastructure, software and skills – is crucial as organizations plan for an AI future. Realizing that this systems approach is hard to build internally, and utilizing partnerships to develop new AI-based solutions will separate the winners. Arrow Electronics has been particularly focused on building a comprehensive portfolio of capabilities to assist our customers in making the AI transition. Bringing together suppliers in various parts of the AI technology stack has enabled us to be a one-stop shop for a variety of AI-related deployments.
While no one is calling for a machine-dominated world, there are bright prospects for machines to further our standard of living and relieve us of redundant and tedious tasks. I, for one, cannot wait for machines to take over all the mundane tasks in my life, like fully driving my car, so I can have more time for myself and my loved ones.
