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Implementing artificial intelligence and managing relationships: 5 ideas from the MIT Sloan Management Review

Implementing artificial intelligence and managing relationships: 5 ideas from the MIT Sloan Management Review

As artificial intelligence matures and expands in companies, leaders across industries are struggling to get everyone involved. At the same time, they must manage customer and employee relationships in the midst of changing expectations in a time of digital transformation.

The latest ideas from the MIT Sloan Management Review consider how to overcome the barriers to AI implementation and go all in on putting AI tools into production. Managers will also learn to know what customers want, how to avoid a toxic workplace, and how to run effective brainstorming sessions.

Overcome 3 common barriers to using AI tools

AI-driven decision-making tools have the potential to increase efficiency, improve service quality, reduce costs and increase revenue. But this only happens if the workers use the tools. Often they do not.

AI projects meet opposition from frontline workers in industries ranging from healthcare to retail, MIT Sloan professorwrites, along with co-authors Mark Sendak and Suresh Balu. This opposition usually stems from three conflicts of interest among AI developers, business management and end users. A more holistic approach to implementation can break through these barriers.

Problem 1: AI tools benefit the organization, not the end user. This is common when organizations use predictive analytics to increase value downstream, as it forces end users to enter data or make decisions that are not related to their role. To address this, AI developers should focus on issues that end users face in their own daily work, while managers should offer concrete incentives to use the tools.

Problem 2: Tools require additional end-user work. Increased engagement with AI tools, especially those outside of workers’ typical technology workflows, only makes the job more difficult. Tools that can automate data collection, testing and validation, and that can provide insight into the applications that workers already use, should minimize the impact on the end-user workload.

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Problem 3: Tools limit end-user autonomy. Prescriptive tools that offer evidence-based decision support – and track if anyone accepts these recommendations – violate end users’ intuitive judgments. AI tools should help end users make decisions while leaving the “final call”. To understand this give and take requires end-user involvement early in the development life cycle.

Read: AI on the front lines

Know the 5 characteristics of an ‘AI Power Center’ company

Almost two thirds of companies have not yet seen the value of their AI investments, and 45% perceive AI as a risk to their business in one way or another. This is because these companies tend to engage in AI and have not yet put their AI tools into production, writes Thomas H. Davenport, a visiting researcher at the MIT Initiative on the Digital Economy, and Randy Bean, CEO of NewVantage Partners .

Mastercard is not one of these companies. Support for AI starts with CEO Michael Miebach and has been built through a combination of acquisitions and internal talent development. The example of Mastercard, a self-described “AI power plant”, suggests that there are five pillars in a company that are fully involved in AI:

  1. Management of products and services. Mastercard started with fraud detection, but plans to use AI on all components of the payment cycle.
  2. Management of internal business operations. Predictive applications support processes ranging from business forecasts (with 99% accuracy) to server maintenance.
  3. Support customers. Mastercard works with corporate customers to identify their own uses for AI – and to create a proof of concept in as little as six weeks.
  4. Pursue AI for good. The company runs AI projects aimed at social development, microfinance and the construction of computer science talents in underserved areas.
  5. Prioritization of ethical AI. In its AI development work, Mastercard emphasizes customer ownership, control over and ability to benefit from its own data.

Read: Becoming an “AI powerhouse” means going all in

Think about these assumptions about what customers want

Prerequisites can steer business leaders towards favorable decisions and align stakeholders according to common views, says MIT Sloan chief researcher explained in a recent webinar. However, conditions also unconsciously amplify bias and filter out innovations that go against the flow. In an ever-changing world, companies need to rethink these 5 common assumptions about customer expectations.

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Customers value the human touch. Many customers actually prefer self-service and believe that a person slows down the interaction.

Personal experiences are better than digital. The digital experience allows companies to reach a worldwide audience while offering better convenience at a lower cost.

People will not pay full price for digital. People pay for value, and convenience is an important part of that value. Offering convenience, digital can provide significant value.

Service restrictions from the pandemic are only temporary. It turns out that certain services cut down during the pandemic, such as daily turndown in hotel rooms, can be overestimated.

The old way was the right one. Traditional business models are not just before the pandemic; They can be before the smartphone, the Internet or even the phone.

When business leaders challenge these assumptions, these are the questions they should keep in mind:

  • Who is the human salesman who helps – the customer, or our inefficient and outdated internal processes?
  • How do we optimize personal and digital interaction for customers, not just ourselves?
  • How do preferences vary by customer segment?
  • When is digital better – and can we pay more, not less, for it?
  • How much did the customers do really need the services we cut down during the pandemic?

See: Thinking about customers’ expectations for 2022 and beyond

Avoid the 5 characteristics of a toxic corporate culture

Many characteristics of a company can contribute to a bad culture, but there is a difference between cultural elements that are annoying or disappointing and those that are really toxic. In a study of more than 1.3 million Glassdoor reviews, MIT Sloan is a senior lecturer and his co-authors identified five common attributes of a toxic corporate culture. These are the characteristics that have the greatest negative impact on how employees assess the corporate culture.

  1. Not inclusive representation of employees by gender, race, sexual identity and orientation, disability and age – combined with a culture of friendship and general unwritten favoritism.
  2. Disrespectful treatment of employees who show a lack of consideration, courtesy and dignity for others.
  3. Unethical and dishonest conduct – or, worse, non-compliance with applicable state and federal regulations.
  4. Cutting work environments where colleagues actively undermine each other.
  5. Abusive management that openly bullies, patronizes or speaks down to employees.
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A toxic corporate culture has a high price. Companies find it more difficult to both attract and retain talent, while employees who remain employed are less productive and more likely to suffer from a chronic illness. And no one is immune: even companies with high corporate culture rankings are likely to contain “pockets of cultural toxicity” with business units, job functions or geographies.

Read: Why every leader needs to worry about toxic culture

Come up with constructive criticism of the creative process

The primary rule for brainstorming sessions – no criticism – dates to the late 1940s. But recent research suggests that constructive criticism may encourage extra creativity and imagination. The key, according to MIT Sloan Associate Professor is to understand the context of the brainstorming session.

In a collaborative context where the goals of the group members are coordinated, criticism can stimulate creativity. In a more competitive session – one where participants, for example, are encouraged to prioritize ideas, or one where groups fall into two camps, such as workers and leaders – criticism is more likely to trigger conflict.

Before implementing a brainstorming session, leaders need to understand the dynamics of the teams coming together. If conflict is likely, organizations can choose one session that includes free-flowing ideas combined with criticism, and then follow up with a session for reviewing ideas. In such a setup, team members are less likely to edit their ideas – and the creative process is less likely to be undermined.

Read: Improve creative brainstorming with constructive criticism

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