Successful adoption of artificial intelligence (AI) at the workplace ultimately depends on employees accepting and embracing their changing role in the future of work, says a recent white paper by global training and development organization Dale Carnegie, “Beyond Technology: Preparing People for Success in the Era of AI". The paper was based on responses from over 3,500 employees.
Mark Marone, director of research and thought leadership for Dale Carnegie and Associates and the author of the paper, believes AI can a significant effect on work culture, employee trust and ethical decision-making. Edited excerpts from an email interview:
How is technology affecting corporate culture and employee engagement?
Let’s start with the positive side because in our research, most people expect AI’s impact to be positive. There is already an array of machine learning applications designed to enhance the employee experience, which should theoretically boost engagement. AI is allowing companies to respond to near real-time sentiment analysis, provide personalized learning opportunities and improve recruiting and onboarding processes. Most people are also quite positive about the potential for AI to handle routine and administrative tasks to allow them to focus on more meaningful work, which should also increase engagement.
At the same time, as AI takes on even more decision-making (in areas such as performance assessments and promotions), it will inevitably change the manager-employee relationship, which we know is a primary driver for engagement. Experts agree that AI will affect nearly everyone’s job. Many companies are undertaking AI projects; some are being open with their workforce about how it may impact the need for human workers, others less so. If AI brings uncertainty about job security, employee engagement is bound to dip.
While there is a great potential for AI to make work more engaging, there is also risk that engagement could be affected if the change is not managed properly.
A critical issue about AI is ethical decision-making. Your thoughts?
AI applications are only as good as the data that are fed into the algorithms. There may be unconscious bias in data which will lead to unfair predictions or recommendations. Leaders will need to be mindful of their responsibility for evaluating decisions for appropriateness. It isn’t, and won’t be, acceptable to put the blame for unethical decisions on AI. We’ve all seen the high-profile examples: Amazon’s AI-driven recruiting algorithm that disadvantaged women, for instance. Humans will continue to have a big role in AI governance. The good news is that AI may help with that too. While AI will inevitably produce biased decisions, the bias may be easier to root out than bias introduced by individual human decision-makers.
What should companies keep in mind before introducing AI at the workplace on a larger scale?
They should take a people-first approach. AI alone won’t win the game. Success is all about the human-machine partnership. This means bringing people into the decision-making process regarding which activities should and should not be automated. We’ve seen examples of failed AI projects when leaders of organizations try to implement AI without being open with their employees. Inevitably, rumours surface which causes fear and distrust. When it comes to AI, leaders should focus their attention on protecting trust, ensuring transparency and building confidence in their workforce that they will be able to transition along with the changing way work will be done.
What’s the importance of trust in an AI-driven workplace?
Trust and respect are always reciprocal. However, it begins with leaders as they are the ones making decisions about digital transformation. Without good faith, transparency that demonstrates the decisions around implementing AI are in the best interest of the company, its people, and its mission, reciprocal trust from employees can’t be expected. At the same time, AI is the future and people have to accept that. Employees need to take a positive attitude toward change, be willing to learn new skills and accept changing roles working alongside machines.