Organizations

Which Jobs Will AI Impact?

The workplace is being disrupted by Artificial Intelligence. A 2019 report by McKinsey Global Institute projects that by 2030, up to 39 million jobs in the US will be displaced by AI. What is the nature of this displacement? In the shadow of AI, how can workers make sure they stay employed and organizations make sure they have the skills they need?

First let’s talk about what AI does for an organization, how it’s used. Recall that today’s AI uses massive artificial neural networks, trained with massive amounts of data. The ‘superpower’ these systems bring to the table is their ability to recognize very complex patterns in digital data. AIs are essentially pattern recognizers. And they are a good fit to today’s world, much of which is represented online as digital data: images, video, business reports, news, financial transactions, customer preferences, ….

AI’s ability to recognize patterns can do lots of useful work. For example AI can be used to augment or replace a human worker’s eyes, ears, brain, or even arms and legs in performing tasks such as:

Industrial inspection, inventory management and warehousing, farming, security, transportation, and elder care
Data entry, customer service, market analysis, travel booking, legal document review, and sentiment analysis
Personal assistance, language translation, news and weather reporting, image captioning, and document summarization
Crime pattern detection, materials and drug discovery, credit checking and fraud detection, business lead generation, and business forecasting
Warehousing, factory assembly, taxi service, delivery service, and long-haul trucking.

Where does this leave us humans?

A short answer: as with other workplace revolutions such as steam engines, mass production, computers, or the internet, some jobs will disappear, new jobs will appear, and many jobs will morph into something different.

AI will tend to replace human labor in jobs that involve routine mental or physical work. For example the 2019 McKinsey report projects that the number of office support jobs in the US will decline from 21 million in 2017 to 18 million in 2030 (an 11% loss), while the workforce will grow 9% over the same period for all jobs in the categories analyzed. Factory jobs, over the same period, are expected to decline by 5%.

Strong job growth 2017 – 2030 is expected in occupational categories that emphasize human relations (health care, 36%; business and legal professionals, 20%; education and training, 18%), as well as in STEM professions (37%).

Of course in a growing economy there can be job growth even in job categories where AI will replace a lot of human labor. For example, McKinsey estimates that 25% of today’s work in customer service and sales will be replaceable by AI by 2030; however the number of jobs in this occupational category will still grow by 10% during that time.

Across all job categories, McKinsey estimates that 25% of human labor expended in 2017 will be replaceable by AI by 2030. This replacement potential ranges from 10% to 39% of the current workforce for every job category. This means few of us will be far from AI’s impact.

How can workers and organizations get ready for the AI transition? A 2019 MIT Sloan School report highlights the need for employers and workers to create and maximize the motivation to learn and adapt over their lifetimes. In a previous blog post I address the need for organizations to adopt an “all-in” approach to AI, integrating organization, IT, and operations.

At the individual level, many workers will need to become familiar with and learn to work with AI. Although AI technology is being developed through the work of specialized researchers with advanced university degrees, the AI research community has made learning about and using the technology surprisingly accessible.

For example Google, Amazon, and Apple all offer free cloud-based environments where workers can learn about AI, and develop and run business tools, without an extensive AI background. A 2019 Northeastern University/Gallup study found that organizations are increasingly developing the internal AI skills they need by training existing staff or through non-degreed interns.

Yes, AI is disrupting the workplace. It is accelerating automation. Workers and organizations must adapt and learn, and then adapt and learn again. But this challenge is accompanied by unparalleled opportunity.

So, how is it going so far? Interesting data point: by analyzing job postings, ZipRecruiter estimates that AI created about three times as many jobs as it destroyed in 2018.

How Will AI Impact Organizations?

We can think of AI as software that helps organizations more effectively reach their goals, e.g., by reducing costs and increasing revenues.

Gaining benefits from AI, or any other innovative technology, requires organizational change. New strategies. New job descriptions. New workflows. New org charts. Training.

What makes AI different? Are the challenges faced by organizations adopting AI different from those encountered in adopting other software innovations?

After all, using computers to revolutionize organizations is nothing new. IBM developed the SABRE reservation database for American Airlines back in 1964, replacing manual file cards with a system that could handle 83,000 reservation requests. Pretty disruptive!

So how is AI changing organizations? Let’s take an example – the financial industry. AI’s ability to find patterns in mountains of data can help financial organizations:

Make more accurate and objective credit decisions by accounting for more complex relationships among a wider variety of factors
Improve risk management using forecasts based on learning patterns in high volumes of historical and real-time data
Quickly identify fraud by matching continuously monitored data to learned behavioral patterns
Improve investment performance by rapidly digesting current events, monitoring and learning market patterns, and making fast investment decisions
Personalize banking with smart chatbots and customized financial advice
Automate processes to read documents, verify data, and generate reports.

To make these improvements using AI, a financial organization needs to undertake the sort of activities needed to introduce any new software into their operations and products, such as:

Establish strategic priorities and budgets
Clarify and communicate objectives and plans with stakeholders
Work with software developers/vendors/users to establish and carry out software/system development projects
Create/modify procedures and organizations to take advantage of the new software
Hire, train, retrain the workforce as needed
Monitor results and adapt as required.

What are the special challenges AI brings to these activities?

The first challenge is AI’s high profile. Managers feel compelled to catch the wave of the future, and workers fear they will lose their jobs. As a consequence:

Managers may undertake AI projects with unrealistic expectations. AI can be extremely effective, however only when there is access to large volumes of data relevant to an operational role that truly benefits the organization
Employees essential to successful adoption of the new systems may stand in the way or quit if they see AI as a threat.

Clearly due diligence is required in the first case, and effective employee engagement in the second.

A second challenge is an “all or nothing” aspect of AI. To reap the benefits of AI, the core AI technology must be fully integrated with an organization’s IT infrastructure and business operations. Notice in the financial organization example above, how many aspects of the organization could be affected by AI. To successfully integrate AI, an organization must be “all in”. To do this requires particularly high levels of communication, investment, and cross-organizational participation.

A third challenge is that with successful adoption of AI, the requirement for personal growth and change is pervasive, up and down the organization. Leaders, engineers, and operators all need to learn and embrace the changes brought about by AI. For many, this can be an exciting opportunity for career growth and more fulfilling jobs. Others will mourn the lost relevance of hard-won experience. The organization must be prepared to invest in training, re-training, and professional development. The more AI takes over routine data gathering and analysis, the more important ‘soft’ skills will be to every worker.

Finally, a fourth challenge is that even a very capable AI can produce unintended results. For example, although AI-based analysis can lend objectivity to credit decisions, training AIs using historical data can promulgate past biases. Also, when highly-trained AIs encounter situations they have never seen before, the results can be unpredictable. This means AIs need human supervisors, and these supervisors are dealing with a whole new kind of employee!

Next: What kinds of jobs will AI impact?

Will AI Take My Job?

AI is smart – it recognizes our faces, drives our cars, translates our languages, wins at Jeopardy, chess, and Go.

AI is scary – as if movies like Terminator aren’t frightening enough, prominent figures such as Stephen Hawking, Elon Musk, and Bill Gates have expressed strong concern that AI might eventually lead to disaster.

And AI is big, too. CEOs across the business spectrum are putting AI in their strategic plans, because they see the competitive advantage being gained by early adopters. An Oxford University study in 2013 predicted that half of US job categories are “at high risk of automation”.

No wonder people look over their shoulders, waiting to be overtaken by some tireless AI with access to unthinkable amounts of digital data and unbelievable computational power!

There is no question that AI is revolutionizing organizations and the world of work. It continues the digital revolution, which disrupted publication, photography, movies, music, telephones, business meetings and more, even creating new definitions of ‘community’ and ‘coworker’.

But thinking of the AI revolution as machines replacing people is a misleading oversimplification, just as it was earlier in the digital revolution. Consider this:

Just like a pocket calculator, AI’s are ‘superhuman’ in very narrow specialities. Even Watson, the seemingly ‘wise’ IBM Jeopardy champion, is a master at learning statistical patterns and relationships in vast collections of human-composed documents. There is enough of a trace of human knowledge in these millions of documents to allow Watson to win at Jeopardy, but Watson does not possess anything like the practical knowledge of a human, even a child.
All human jobs require adaptability, creativity, and social interactions that are way beyond AI in the foreseeable future. We may think what makes us special in our job is a rare talent for data collection and analysis, but that talent would be nothing but a parlor trick without the human ability to apply, adapt, learn, and interact.

These disruptive AI machines need people. In the first place, they need people to build and maintain them. In the second place, the masterfully calculated result an AI might give can only be just a part of any job. The AI’s part may be pivotal, enabling, competitive, disruptive. Can it do your job? No. Will it change your job? Yes.

So as AI’s come after our jobs, I think we have a choice. If we insist on doing our job the way it’s always been done, we might lose our job. If we embrace AI as the empowering tool it can be, we can elevate our job to one that contributes more value to our organization and frees us to do work that is more challenging and satisfying.

The Thinking Organization

This pyramid summarizes the Thinking Teams view of a successful organization, an organization effectively moving toward its goals, powered by collaborating teams of wholehearted individuals. The pyramid represents building from foundational elements; its layers show focus areas for organizational improvement and growth. Starting from the base:

Self-Aware, Productive Individuals – a wonderful alignment happens when an organization helps its members participate in a way that connects with and acknowledges their full selves, not just the conscious tip of the mind’s iceberg (The Committee in Your Head, The Power of Alignment)

Open, Respectful Person-Person Communication – when teams learn to communicate, not from the deceptively efficient but narrow perspective of concrete positions, but from an expanded awareness of shared goals and the potential for mutual learning, each team member moves closer to full potential and contribution (Apples and Oranges, Another Iceberg)

Focused, Agile, Managed Teams – when the natural tools of human cooperation are focused and enabled by agile structure, the team becomes greater than the sum of its members (Hive Mind, Bendable Concrete, Being Rational About Irrationality )

Thriving Enterprise Led With Vision – when leaders embrace the sometimes contradictory facets of their organization (Corrective Lenses), they can expand their options and tailor effective action by tending to all four aspects of their organization*, their organization as:

“Factory” – creating structure that mutually supports individual and organization (Happy Cogs, Taking Chances )
“Family” – Holding and fostering organizational values that transcend the daily To-Do list (The 26 Hour-a-Day Manager)
“Arena” – creating a transparent, fair space to engage divergent interests and allocate scarce resources (Clean Politics)
“Theater” – articulate the symbols that connect an organization’s mission to meaning and value for team members and stakeholders (Theater of Symbols)

–Tom

*Bolman, Lee G. and Deal, Terrance E. Reframing Organizations – Artistry, Choice, and Leadership. San Francisco: Jossey-Bass A Wiley Imprint, 2003.