ARTIFICAL INTELLIGENCE AND PRIN-AGENT PROBLEM 1

An Analysis of Managerial Coordination:

Will Artificial Intelligence Technology Counter the Principal Agent Problem?

Alegra N Horne

Harvard University Extension School

This paper was prepared for ECON S-1620 Organizations, Management Behavior &

Economics taught by Professor Charles A. Moran.

ARTIFICAL INTELLIGENCE AND PRIN-AGENT PROBLEM 2

Introduction

It is not surprising that around the world organizations are finding themselves rife

with principal–agent problems. The interdependence and interconnections of organizations

has created a large pool of agency relationships in which monitoring is near impossible.

Notwithstanding, high ethical standards and the power of incentives should have driven

agents to align their interest with those of their owners. Unfortunately, ethical standards or

the power of incentives has significantly addressed the principal-agent dilemma.2 In fact,

studies show, many employees who witness wrongdoing do not report it, and worst, many

engage in the illegal activity to get ahead if they believed they would not be caught.2

Interestingly, these patterns exist even though data suggest trust is the quality most investors

value when hiring senior management.1

Since the 2000s, the principal-agent dilemma has become a critical hurtle facing

organizations’ around the globe. A quick glance through Time, Forbes, The New York

Times, or The Wall Street Journal and a principal-agent problem is bound to make the front

page. The principal-agent problem is relevant to any shareholder and top management team

of publically traded organizations.

Generally, the problem arises because of a misalignment between the objectives of

shareholders and the objectives of management. Often, this mismatched alignment, stems

1 Shah, Sunit N. (2014). The Principle-Agent Problem in Finance (a summary). The CFA Institute Research Foundation Publishing. Retrieved from https://www.cfainstitute.org/learning/foundation/research/Documents/principal-agent_problem_in_finance.pdf.

ARTIFICAL INTELLIGENCE AND PRIN-AGENT PROBLEM 3

from lack of investments generating appropriate free cash flow, differences in risk appetite,

the time horizon of returns, and management consumption.2 The literature is replete with

theoretical assumptions, compensation schemes, and industry practices to address the

relevance of this topic to organizations and for societal benefit. However, this paper

introduces the provocation needed to reevaluate current practices in light of ongoing

advancements in pattern recognition simulated intelligence technology.

Discussion

According to the principal-agent theory, the central question is ‘how’ should the

principal design the agent’s reward structure? This question has taken center stage since the

financial meltdowns of the 2000’s. Many areas of an organization’s activities do not rely on

market interactions but instead are coordinated via middle-to-senior management layers.

Thus, creating opportunities for managers and workers to pursue their own goals, at the

expense of company performance.

The Perils of Executive Compensation

To alleviate this issue, shareholders and boards of directors incentivize management

contribution to improve firm profitability and efficiency considering its best available

opportunities and the potential risks. Therefore, the use of incentives is necessary because

contribution is very difficult to measure directly. Traditionally CEO compensation

incentives and payouts are fettered to lagging performance indicators; however, with

2 Douma, Sytse and Hein Schreuder (2013). Economic Approaches to Organizations (5th ed.). London, UK: Pearson. Print.

ARTIFICAL INTELLIGENCE AND PRIN-AGENT PROBLEM 4

advanced technology patterns, a real-time monitoring platform must replace such business

metrics to better assess management and firm performance for establishing incentives

packages.

Milton Friedman put it well when he said one of the biggest risks we face today is

that management will cease to want to take risks.4 And I think not only in compensation but

more broadly in examining corporate governance, we must be careful not to diminish the

motivation for risk taking and entrepreneurship that drives so many of our corporate leaders.3

While Milton Friedman, an avid compensation and shareholder proponent, would

receive great headwinds today from both sides of the political spectrum on executive

compensation schemes. Increasingly, Americans are speaking out about what they see as an

uneven playing field emerging. Suggesting that severance packages for under-performing

CEOs reflect a broader trend in the U.S. economy.6 Advocating that if shareholders want to

take action on executive compensation, they should make sure that executives’ interests are

aligned with their own; they should look for bonus schemes that link payout to targets for

metrics like Total Shareholder Returns (TSR).4,6

3 Williams, Sydney (2013). CEO Pay Ratio and Social Responsibility. Austrian Economics Center. Retrieved from http://www.austriancenter.com/2013/10/29/ceo-pay-ratio-and-social-responsibility/

4 Grossman, Sanford J. and Oliver D. Hart (1983). An Analysis of the Principal-Agent Problem.

Econometrica, Vol. 51(1): 7 – 45. Retrieved from: http://www.dklevine.com/archive/refs4391749000000000339.pdf, accessed on June 22, 2016.

ARTIFICAL INTELLIGENCE AND PRIN-AGENT PROBLEM 5

In the wake of the financial crisis, U.S. legislators have already acted to implement

new rules regarding so-called “golden parachute” payments for departing executives.6 These

rules however, apply to cash payments only, and not to stock-linked compensation.6 As the

most recent data show, the new rules have done little to clamp down on excessive CEO

severance packages.6 Raising the awareness of executives at publicly traded companies that

if they fail to align pay policies with performance, regulators might be inclined to intervene

to change the rules of the game.6

Lloyd Doggett, a Democratic representative of Texas and senior member of the

House Ways and Means Committee, called outsized severance packages for executives

“outrageous.” “The whole concept that the only way to get rid of bad management is to buy

them off is fundamentally wrong.”5

Time for a Methodology

With so much turmoil from public scrutiny, shareholder frustration, and every-

changing environmental complexities facing corporate managers today. The discovery of

comprehensive solutions to align shareholder-executive compensation incentives to financial

performance metrics is imperative. Arguably, shareholders and board members of

organizations want to promote financial performance, so they compensate executives directly

for it.7 However, with the increasing risks of resource scarcity and globalization posing to

5 Flannery, Nathaniel P (2011). Paying for Failure: The Costs of Firing America’s CEOs. 2016 Forbes.com. Retrieved from http://www.forbes.com/sites/nathanielparishflannery/2011/10/04/paying-for-failure-the-costs-of-firing-americas-top-ceos/print/

ARTIFICAL INTELLIGENCE AND PRIN-AGENT PROBLEM 6

organizations6, what about monitoring performance and compensation packages by way of

simulated technology tracking?

When it comes to executive pay, the debate of how to link compensation continues.

One indicator overlooked is executive overconfidence and compensation structures are

supported by the findings that firms offer incentive-heavy compensation contracts to

overconfident CEOs to exploit their positively biased views of firm prospects.8 As reported,

overconfident CEOs receive more option-intensive compensation.

In addition, the pay-for-performance metrics—particularly the idea of paying

executives with stock to align their interests with shareholders—may even have amplified

that trend.7 Ignoring behavioral factors such as overconfidence when designing

compensation incentives has a substantial influence on shareholder returns or worst could

result in corporate failure. Yet, a system to incorporate or consider management behavior

and motives remains unavailable.

A New Intuitive for Advanced Technology

The current shortcoming in theories and business practices are imploring

technological advances to solve these issues. One solution presented in this paper to address

6 Prendergast, C (1999). The Provision of Incentives in Firms. Journal of Economic Literature, 37(1): 7 – 63. Retrieved from http://www.jstor.org/stable/2564725

7 Eavis, Peter (2014). Executive Pay: Invasion of the Supersalaries. The New York Times

Company. Retrieved from http://www.nytimes.com/2014/04/13/business/executive-pay-invasion-of-the-supersalaries.html

ARTIFICAL INTELLIGENCE AND PRIN-AGENT PROBLEM 7

the gap(s) between compensation and performance rests with new advances in artificial

intelligence technology1. To that end, what is artificial intelligence and how can it help?

1Artificial intelligence (AI) is machine intelligence generated by human algorithms.

In computer science, an ideal “intelligent” machine is a flexible rational agent that perceives

its environment and takes actions that maximize its chance of success at some goal. Even as

companies, deliver lack-luster returns to shareholders there remains an opportunity to correct

these flaws. The solution presented here rest with using technology to monitor management

performance tied to a real-time system of leading indicators to adjust compensation plans or

providing warnings of potential issues in performance.8

With the advent of advanced artificial intelligence computing, the potential for

companies to incorporate the technology to track executive performance and their bonus

structures is a game changer. Technology statistics point to not only an emerging trend, but

also the varying degrees of transparency and rigor with which corporations could link

executive compensation to goals and results, and using the next level of algorithms should be

the nature progression for this path.

One exemplary example is the Hong Venture Capital firm, which has tied its board

activities to computing algorithms to provide additional board support, named VITAL.9 This

8 AI Impacts (2016). Future of Life Institute FLI-RFP-AI1 program, grant #2015-143901 (5388). Retrieved from: http://aiimpacts.org/, accessed on June 22, 2016.

9 Wile, Rob (2014). A Venture Capital Firm Just Named An Algorithm To Its Board of

Directors – Here’s What It Actually Does. Business Insider – Finance. Retrieved from http://www.businessinsider.com/vital-named-to-board-2014-5

ARTIFICAL INTELLIGENCE AND PRIN-AGENT PROBLEM 8

firm is a cutting-edge example of one of the potential avenues to the use of 1AI technology.

Other, potential benefits documented in the literature are presented below to demonstrate

trade-offs and gains.

Aggressively linking executive compensation should provide results in the following

improvements:

• Financial benefits10

o Given the nature of the field, there is little data yet to show the

correlation between this practice and better long-term financial

profitability.

• Reputation and culture benefits10

o Linking compensation to artificial technology is a powerful marker of a

company leadership.

o Additionally, this practice can serve as a powerful tool to increase

accountability and promote action around performance goals, an

objective sought across the globe to increase accountability and

positively influencing our culture.

o Employees across the company are increasingly incentivized to put at

the center of the way they do business.

10 Dvorsky, George (2014). Can We Build an Artificial Superintelligence That Won’t Kill Us? IO9 Gizmodo. Retrieved from http://io9.gizmodo.com/can-we-build-an-artificial-superintelligence-that-wont-1501869007

ARTIFICAL INTELLIGENCE AND PRIN-AGENT PROBLEM 9

As with everything, now is a good time to think about implementing such a powerful

tool to position your company for success in this new environment. While advanced AI

technology tracking could prove to be an imperfect tool, providing an argument that such a

tool could dent the morale of executives and cause their companies to underperform. It is

possible to find hard-working manager willing to meet the challenge and who are willing to

measure themselves by new metrics standards.

ARTIFICAL INTELLIGENCE AND PRIN-AGENT PROBLEM 10

Conclusion

A McKinsey report11, suggest the degree of awareness is greater today in the face of

globalization and tightening market share. Therefore, next decade12 will be an exciting time

for organizations, which must perform at reliable and successful levels to build and maintain

market staying power. One indicator of organizational performance are market outcomes.

Thus, the use of artificial intelligence to solve the world’s biggest problems is only a leap

away.13

11 Mauldin, John (2014). Here’s How Robots Could Change the World by 2025. Business Insider – Finance. Retrieved from http://www.businessinsider.com/heres-how-robots-could-change-the-world-by-2025-2014-8

12 Smith, Aaron and Janna Anderson (2014). AI, Robotics, and the Future of Jobs.

Copyright 2016 Pew Research Center. Retrieved from http://www.pewinternet.org/2014/08/06/future-of-jobs/

13 Wikipedia The Free Encyclopedia ( 2016). Wikipedia The Free Encyclopedia. Version 1.

Wikimedia Foundations, Inc. Retrieved from https://en.wikipedia.org/wiki/Artificial_intelligence.