The AI equation for realizing value: Balancing logic and emotion
- Posted on August 6, 2024
- Estimated reading time 10 minutes
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One way to think about the challenges and opportunities of AI adoption and value realization is to compare it to driving a car. A car is a product of engineering, technology, and logic. It can offer many benefits to drivers and passengers, such as speed, convenience, safety, and comfort. However, driving a car also requires certain skills and conditions to be effective, such as driving literacy, road awareness, problem-solving, and ethical behavior. Moreover, driving a car is not only a technical or rational process, but also an emotional and human one. It involves trust, feeling empowered and involved, relief of stress and boredom or creation of joy when driving well.
If organizations really want to deliver maximum benefits through the daily activities of their people, we need to take a holistic approach that considers both the logical need for AI and the emotional human factors that need to be addressed. According to our AI research, the level of trust with AI is much higher amongst IT teams than the rest of the business, with 54% of IT professionals completely trusting the results of AI, while only 42% of professionals in business functions (e.g. Finance, Sales, Communications, HR) completely trust AI. Our research also showed that trust increases with training and experience. The top reason for those business professionals having less trust than their IT colleagues is a very human response: they believe that humans train AI, and humans are fallible. Additionally, employees can be suspicious of the motivations of business leaders as they experiment with AI if they don’t feel involved in the process. Empowering all employees to effectively use AI and innovate with it can unlock a step change in value delivered – both for the individual and the organization.
What is the key to unlocking the full potential of AI and transforming our organizations, our work, and our value creation? In this article, we will share key success factors such as:
- Involve employees and leaders early
- Design AI solutions with a people first approach and aim to improve their experience and productivity
- Make AI specific and relevant for the business context and goals
- Train and encourage employees to use AI effectively and responsibly, by prompting, experimenting, sharing and being resilient
- Create a culture of continuous improvement and innovation, where feedback and data from employees generate new ideas and opportunities for AI
The importance of investing in employee experience alongside AI
AI can boost logic and analysis, but organizations also need to invest in the creativity and emotion of their employees. Employee experience is how employees feel and think about their work and employer. A positive experience can drive innovation, engagement, and productivity, and help attract and retain talent. A study by MIT CISR shows that companies that invest in employee experience achieve better outcomes, such as 71% better customer experience, 56% more revenue from innovation, 19.6 percentage points higher revenue growth, and 15.3 percentage points higher net margin. Experience management enables modern work, productivity anywhere, human potential, a healthy workforce, cost and risk reduction, and return on investment. Organizations should use AI to enhance, not replace, the human aspects of work, and foster a culture that values and supports the human elements of AI.
Aligning AI with human values, emotions, and ethics
One of the challenges of managing the emotions of AI at scale is how to ensure that the technology we use and create reflects our values and ethics and does not harm or exploit others.
As part of an effort to explore the potential of AI for enhancing both individual and organizational productivity for ourselves, we’ve encouraged Avanade employees to experiment with new ways of working so they can focus on more strategic tasks. As part of an Early Access Program (EAP) for Microsoft Copilot we learned a great deal about ourselves. One of our key findings was how AI aligned with our values. Of those that participated in the EAP, 88% agreed Copilot for Microsoft 365 aligned with Avanade’s corporate values, but only 65% agreed it aligned with individual personal values. So why the disparity?
AI systems can generate emotional responses in humans, such as trust, empathy, or fear, depending on how they are designed and deployed. For example, chatbots, virtual assistants, and social robots can use natural language and emotional cues to communicate and persuade users, but they can also manipulate, deceive, or coerce them if they are not transparent about their intentions and limitations.
To avoid these risks, we need to adopt a people-first approach to AI, where we consider the impact of AI on human well-being, dignity, and rights. We need to design AI systems that are human by design, meaning that they respect human values, norms, and preferences, and that they are accountable, explainable, and fair. We also need to empower humans to control and shape AI systems, rather than being passive consumers or subjects of them. This requires education, literacy, and broad participation in the development and governance of AI.
In the case of Avanade’s EAP program, the disparity between corporate values and personal values led to us implementing tailored engagement, learning and application programs for each employee to help them work and innovate responsibly with generative AI. As the tool becomes a staple in the digital workflow, sustaining and deepening trust hinges on Copilot for M365's ability to grow with the user, offering transparency and accountability that go hand in hand with its technical capabilities.
How to prepare for the future of work with generative AI
AI can augment human capabilities, automate tasks, and generate novel outcomes that were previously unimaginable. But it can also disrupt existing roles, processes, and norms, requiring new skills, mindsets, and behaviors from employees.
The democratization of AI with tools such as Microsoft Copilot brings unprecedented challenges for organizations and their people to responsibly innovate and work with AI through continual change. While employees are generally optimistic about AI and confident in their organization's technical capabilities, less than half say their organization has adequate human capital, workforce planning, and responsible AI policies in place.
Avanade’s research also finds that 63 percent of business and IT professionals believe their organization will need to enable employees with some new skills or a completely new set of skills by the end of 2024 to achieve benefits from generative AI. That means huge upskilling and a renewed focus on digital literacy will be needed. How can we guard against another wave of digital exclusion?
AI and the accelerated pace of change is intensifying the spectrum of emotions that individuals are experiencing. Some employees may feel excited, curious, and empowered by the possibilities of AI, while others may feel anxious, threatened, and overwhelmed by the uncertainty and complexity of AI. Through our research we’ve been able to identify significant gaps between IT and business professionals when it comes to optimism of how AI will impact them. By virtually every measurement (empowerment, innovation, isolation, job satisfaction and frustration), employees in business functions lag behind their IT colleagues on AI optimism. When groups of employees are experiencing these extremes of emotions in parallel, it impacts their capacity to collaborate and perform, as well as the broader culture and effectiveness of the organization.
Managing employee emotions with empathy and involvement
One of the keys to support employees in the era of generative AI is to manage their emotions with empathy and involvement. Both can help to build trust, engagement, and loyalty among employees, as well as to foster a positive and inclusive work environment.
By managing employee emotions with empathy, organizations can help their people to cope and thrive in the fast-changing and uncertain world of work. Empathy can also enable organizations to leverage the full potential of generative AI, by ensuring that it is aligned with the values, needs, and interests of their employees, and that it enhances their creativity, productivity, and satisfaction.
A high ‘involvement’ approach to AI adoption and ideation, where employees are encouraged to choose and use AI technologies based on their own needs and preferences, can create a people-centric AI culture in the organization. Instead of imposing AI solutions and use cases from the top down, organizations should empower their employees to explore, experiment, and collaborate with AI in their daily work. Furthermore, once individuals are shown the basics of key AI technology such as Microsoft Copilot, organizations have the opportunity to set up ideation rhythms in the business where representatives are asked to brainstorm opportunities for AI to improve work and experiences. Such an approach can foster more value creation and innovation, improve digital and AI maturity and increase the trust and acceptance of AI among the workforce. It’s this same approach that Avanade was recognized for in winning the “Best AI Consulting Service Provider” award for our Disrupt Avanade program, which explores, builds, and adopts AI across all business functions, with a ‘people first’ mindset and responsible AI practices. By involving a diverse range of employees in the AI process, from ideation to implementation, organizations can leverage their collective intelligence, creativity, and skills, and align AI with their values and goals.
Key success factors to build a people-centric AI culture in your organization
Having worked with many organizations globally to enhance their AI culture, we see there are some key success factors in delivering benefit from enhanced AI usage:
- Involve the broader business and leadership early: AI affects all employees, not just IT, so the development of AI principles, tools and support approaches must involve the whole organization to be successful. Your senior leadership should understand the implications of AI and be involved in generating a point of view on AI for the organization. Your people should have the opportunity to experiment, ideate and share ideas on AI, as well as having a say in how they are supported to use it well.
- Visibly adopt a people first approach to AI: Follow three principles - lead by negotiation, not by direction; communicate the value of AI in the specific context of each employee; and embed responsible AI processes that reflect the organization's values and amplify the human attributes that make us uniquely human.
- Make it specifically real and tangible over time: Don’t just train your employees with the basics. Set up a long-term program of learning that is tailored to different role types, team activities to apply skills and tools within real work scenarios, gamification and competitions to accelerate uptake and innovation, measurement and recognition of specific contributions – all actively supported by visible leadership and locally skilled champions.
- Focus on a few key behaviors needed from employees: Employees need to be supported to learn some fundamental skills (e.g. prompting, responsible use) to utilize AI effectively. As important are some fundamental ‘cultural’ behaviors that should be encouraged – showing resilience when AI doesn’t always work the first time; experimenting with AI to find more value; sharing good AI ideas and use cases. These few key behaviors can significantly uplift AI culture.
- Create a rhythm of continuous EX improvement: Your first experiments with AI, if done right, can be the engine for ongoing ideas and improvement. If you have trusting and engaged employees, get them involved in ‘what else’ conversations. Collect employee experience metadata via sources such as Microsoft Viva Insights, Service Now tickets, engagement surveys/ focus groups and HRIS to inform them of trends, opportunities and progress. Recognize good ideas.
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