Digital Distrust: Change Management in the AI era
The wide-scale adoption of Artificial Intelligence (AI) is accelerating in financial services, with firms already using AI for customer services chatbots, fraud detection, and trading to name but a few.
For banking executives who have struggled to restore profitability in the aftermath of the financial crisis, AI is a welcome ray of hope to achieve cost-reduction targets. Past CEOs of Deutsche Bank and Citigroup have publicly commented on the potential to replace 30-50% of the workforce with AI solutions.
However, employees are reluctant to put their faith in AI. Employees are naturally wary given the volume of white papers from consultancies and think-tanks that herald mass disruption to existing jobs, as well as high profile instances of AI going rogue (think Microsoft’s inflammatory Tay chatbot, or Uber’s red-light-running self-driving cars).
AI is commonly misunderstood as a blanket solution for all problems that will lower headcount, rather than being a human- potential enabler that will free us from mundane tasks and allow us to focus on more interesting and creative work. How do we overcome the challenge of employee perception, and how will AI impact our work as Change Managers?
First, we must address the root causes of distrust to win staff over. People have difficulty understanding AI because it is complex and can process vast quantities of data to arrive at conclusions, seeing patterns where humans cannot. Machine learning enables programs to self-improve as they operate, potentially to the point where outcomes are difficult to reverse-engineer and explain. It is imperative that employees can fathom what is inside the ‘black box’ of AI. Ongoing educational campaigns, coupled with visualisation tools that help users to break down the decisions reached, can go a long way in demystifying the technology.
Employees in non-technical roles need to be involved from the start in AI initiatives. They should be allowed to experiment, change parameters and observe the outcomes. This leads to users/employees feeling involved in the creation of the solution – partners of it, rather than replaced by it. It also has the advantage of leveraging a wider pool of experience and ideas, capturing potential new uses and enhancements that might otherwise be missed. Employees need to be sold on the benefits – to them personally, not just the organisation as a whole – early on. Given sufficient opportunity to interact with AI, they can become enthusiastic about the value it can add to their role and reassured by the limitations of its capabilities.
Secondly, as Change Managers, we must adopt AI tools ourselves and lead by example. AI could be used to help with tasks, such as anonymously scanning large volumes of communications to sense organisational sentiment or to help identify and map additional stakeholders. An AI assistant could provide timely reminders of groups you haven’t spoken to in a while, or help to maximise your influence by suggesting appropriate styles to adopt for a particular audience. Training and development needs could be better met through adaptive learning features and personalised courses that help the individual best adjust to the change.
AI capabilities within project management are continually improving. AI is already able to automate tasks and reporting, and this is likely to expand to cover forecasting and even team management. In future, project management AI will be able to reassign tasks based on its understanding of the work required, team strengths and weaknesses, and staff utilisation. Imagine how much more effective and fulfilled you could be as a Change Manager if you cut out the administrative tasks and focused more of your time on creative aspects of the job and making greater use of your specialist skills.
Familiarity with AI on the part of the Change Manager will make it easier to understand (and so explain to others) the potential applications. It will also increase productivity, enabling enhanced insights and more targeted responses to resistance against change.
Lastly, the structure and composition of the workforce is likely to change, as is the nature of management’s role within it. Managers of the future will be those who are best able to stimulate the creativity of others, bringing together diverse ideas into innovative solutions. As builders of the conceptual onion, they will layer ideas upon ideas whilst encouraging experimentation, imagination and collaboration among colleagues.
Naturally this will change the way ‘leadership’ in the workplace is viewed; it will become less about the ability to oversee management processes that maintain and steadily improve current performance, and more about visionary thinking, broad networking, people development, coaching, motivation, fostering cooperation and demonstrating empathy. Leaders of the future are likely to spend considerably more time interacting with colleagues as AI frees their time from administrative duties and therefore exceptional people skills will be required in them.
As leaders throughout the change cycle, it will be down to Change Managers to develop these creative and people-focused skills in the BAU managers they work with, and to effectively do that they themselves need to adapt to both the technology and the new employee skills matrix.
AI is developing at a rapid pace and will have a significant, irreversible impact on the way work is performed across industries. It has many benefits to offer, but successful implementation will require staff to embrace a technology that is currently viewed as a threat, misunderstood, or both. The pace of change will increase, and the way AI is managed will need to keep up; this will require modernising or completely overhauling current strategies, tools and techniques. Early engagement with staff, transparency around AI capabilities and people-centric leadership can all help to ensure AI becomes a workforce ally, not adversary.
