AI May Soon Replace Even the Most Elite Consultants
Note: Originally published at [Harvard Business Review](https://hbr.org/2017/07/ai-may-soon-replace-even-the-most-elite-consultants?referral=03759&cm_vc=rr_item_page.bottom" Target=" Blank). Republished by the author
Amazon’s Alexa just got a new job. In addition to her other [15,000 skills](https://techcrunch.com/2017/07/03/amazons-alexa-passes-15000-skills-up-from-10000-in-february/?utm_source=CB+Insights+Newsletter&utm_campaign=e8f51e0ccf-FriNL_6_23_2017&utm_medium=email&utm_term=0_9dc0513989-e8f51e0ccf-89106385" Target=" Blank) like playing music and telling knock-knock jokes, she can now also answer economic questions for clients of the Swiss global financial services company, UBS Group AG.
According to the Wall Street Journal (WSJ), a [new partnership between UBS Wealth Management and Amazon](https://www.wsj.com/articles/alexas-new-avatar-financial-adviser-1495550410?mg=prod/accounts-wsj" Target=" Blank) allows some of UBS’s European wealth-management clients to ask Alexa certain financial and economic questions. Alexa will then answer their queries with the information provided by UBS’s chief investment office without even having to pick up the phone or visit a website. And this is likely just Alexa’s first step into offering business services. Soon she will probably be booking appointments, analyzing markets, maybe even buying and selling stocks. While the financial services industry has already begun the shift from [active management to passive management](http://www.wsj.com/graphics/passive-investing-five-charts/" Target=" Blank), artificial intelligence will move the market even further, to management by smart machines, as in the case of [Blackrock](https://www.nytimes.com/2017/03/28/business/dealbook/blackrock-actively-managed-funds-computer-models.html?mcubz=2" Target=" Blank), which is rolling computer-driven algorithms and models into more traditional actively-managed funds.
But the financial services industry is just the beginning. Over the next few years, artificial intelligence may exponentially change the way we all gather information, make decisions, and connect with stakeholders. Hopefully this will be for the better and we will all benefit from timely, comprehensive, and bias-free insights (given research that human beings are [prone to a variety of cognitive biases](https://techcrunch.com/2015/09/24/the-surprising-bias-of-venture-capital-decision-making/" Target=" Blank). It will be particularly interesting to see how artificial intelligence affects the decisions of corporate leaders — men and women who make the many decisions that affect our everyday lives as customers, employees, partners, and investors.
Already, leaders are starting to use artificial intelligence to automate mundane tasks such as calendar maintenance and making phone calls. But AI can also help support more complex decisions in key areas such as human resources, budgeting, marketing, capital allocation and even corporate strategy — long the bastion of bespoke consulting firms such as McKinsey, Bain, and BCG, and the major marketing agencies.
The shift to AI solutions will be a tough pill to swallow for the corporate consulting industry. According to recent research, the [U.S. market for corporate advice alone is nearly $60 billion](https://blogs.wsj.com/cfo/2017/05/23/u-s-consulting-spending-tops-58-billion-in-2016/" Target=" Blank). Almost all that advice is high cost and human-based.
One might argue that corporate clients prefer speaking to their strategy consultants to get high priced, custom-tailored advice that is based on small teams doing expensive and time-consuming work. And we agree that consultants provide insightful advice and guidance. However, a great deal of what is paid for with consulting services is data analysis and presentation. Consultants gather, clean, process, and interpret data from disparate parts of organizations. They are very good at this, but AI is even better. For example, the processing power of four smart consultants with excel spreadsheets is miniscule in comparison to a single smart computer using AI running for an hour, based on continuous, non-stop machine learning.
In today’s big data world, AI and machine learning applications already analyze massive amounts of structured and unstructured data and produce insights in a fraction of the time and at a fraction of the cost of consultants in the financial markets. Moreover, machine learning algorithms are capable of building computer models that make sense of complex phenomena by detecting patterns and inferring rules from data — a process that is very difficult for even the largest and smartest consulting teams. Perhaps sooner than we think, CEOs could be asking, “Alexa, what is my product line profitability?” or “Which customers should I target, and how?” rather than calling on elite consultants.
Another area in which leaders will soon be relying on AI is in managing their human capital. Despite the best efforts of many, mentorship, promotion, and compensation decisions are undeniably political. Study after study has shown that deep biases affect how groups like women and minorities are managed. For example, women in business are [described in less positive terms than men](https://hbr.org/2017/05/we-recorded-vcs-conversations-and-analyzed-how-differently-they-talk-about-female-entrepreneurs" Target=" Blank) and receive less helpful feedback. Minorities are [less likely to be hired](http://fortune.com/2014/11/04/hiring-racial-bias/" Target=" Blank) and are [more likely to face bias](https://hbr.org/2017/01/evidence-that-minorities-perform-worse-under-biased-managers" Target=" Blank) from their managers. These inaccuracies and imbalances in the system only hurt organizations as leaders are less able to nurture the talent of their entire workforce and to appropriately recognize and reward performance. Artificial intelligence can help bring impartiality to these difficult decisions. For example, AI could determine if one group of employees is assessed, managed, or compensated differently. Just imagine: “Alexa, does my organization have a gender pay gap?” (Of course, AI can only be as unbiased as the data provided to the system.)
In addition, AI is already helping in the customer engagement and marketing arena. It’s clear and well documented by the [AI patent activities](http://www.ipwatchdog.com/2016/12/22/big-tech-companies-increase-patent/id=76019/" Target=" Blank) of the big five platforms — Apple, Alphabet, Amazon, Facebook and Microsoft — that they are using it to market and sell goods and services to us. But they are not alone. Recently, HBR documented [how Harley-Davidson was using AI to determine what was working and what wasn’t working across various marketing channels](https://hbr.org/2017/05/how-harley-davidson-used-predictive-analytics-to-increase-new-york-sales-leads-by-2930?utm_campaign=hbr&utm_source=facebook&utm_medium=social" Target=" Blank). They used this new skill to make resource allocation decisions to different marketing choices, thereby “eliminating guesswork.” It is only a matter of time until they and others ask, “Alexa, where should I spend my marketing budget?’’ to avoid the age-old adage, “I know that half my marketing budget is effective, my only question is — which half?”
AI can also bring value to the budgeting and yearly capital allocation process. Even though markets change dramatically every year, products become obsolete and technology advances, and [most businesses allocate their capital the same way year after year](http://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/how-to-put-your-money-where-your-strategy-is" Target=" Blank). Whether that’s due to inertia, unconscious bias, or error, some business units rake in investments while others starve. Even when the management team has committed to a new digital initiative, it usually ends up with the scraps after the declining cash cows are “fed.” Artificial intelligence can help break through this budgeting black hole by tracking the return on investments by business unit, or by measuring how much is allocated to growing versus declining product lines. Business leaders may soon be asking, “Alexa, what percentage of my budget is allocated differently from last year?” and more complex questions.
Although many strategic leaders tout their keen intuition, hard work, and years of industry experience, much of this intuition is simply a deeper understanding of data that was historically difficult to gather and expensive to process. Not any longer. Artificial intelligence is rapidly closing this gap, and will soon be able to help human beings push past our processing capabilities and biases. These developments will change many jobs, for example, those of consultants, lawyers, and accountants, whose roles will evolve from analysis to judgement. Arguably, tomorrow’s elite consultants already sit on your wrist (Siri), on your kitchen counter (Alexa), or in your living room (Google Home).
The bottom line: corporate leaders, knowingly or not, are on the cusp of a major disruption in their sources of advice and information. “Quant Consultants” and “Robo Advisers” will offer faster, better, and more profound insights at a fraction of the cost and time of today’s consulting firms and other specialized workers. It is likely only a matter of time until all leaders and management teams can ask Alexa things like, “Who is the biggest risk to me in our key market?”, “How should we allocate our capital to compete with Amazon?” or “How should I restructure my board?