AI offers companies a competitive advantage by enabling them to enhance productivity, streamline business processes, enhance marketing strategies, attract specialised talent, enable digital transformation and achieve other benefits. However, the successful implementation of AI goes beyond just technology. It is crucial for organisations to effectively integrate AI solutions into their operations and ensure employee adoption in their daily work. This task, however, is not always easy to accomplish.

AI tools represent a significant departure from the established norms and practices. Furthermore, they can disrupt the usual course of business by altering familiar processes and activities. These factors often give rise to resistance, a natural human response that poses a risk to AI initiatives and investments.

When faced with extensive changes within an organisation, the only way to move forward is through effective change management. This is particularly important in the context of AI, which is an evolving and complex field.

“In the sphere of business, AI is poised to have a transformational impact on the scale of earlier general-purpose technologies,” Erik Brynjolfsson and Andrew McAfee explain in the Harvard Business Review. “Although it is already in use in thousands of companies around the world, most big opportunities have not yet been tapped. The effects of AI will be magnified in the coming decade in virtually every industry. The bottleneck now is in management, implementation and business imagination.”

The introduction of AI and digital transformation disrupts not only workflows and processes but also has the potential to impact entire job roles, leading to feelings of apprehension and unease among employees.

Every AI or digital transformation initiative brings about change in the workplace, and the effectiveness of its implementation hinges on having a robust change management strategy in place.

What is change management?

Change management is a structured approach to assist organisations and individuals in effectively implementing new initiatives, such as the introduction of AI solutions or managing reorganisations and restructuring. Its main objective is to ensure the success of these initiatives by creating a detailed plan to launch and monitor the impact of new technologies.

In the context of AI implementation, change management serves as a roadmap that guides businesses through the process of change. It helps anticipate potential challenges and ensures that companies can fully leverage the benefits of AI technology. Furthermore, it focuses on involving and supporting employees throughout the transition, fostering open communication, addressing resistance and harnessing the new capabilities that AI brings.

By prioritising the people aspect of change, organisations can navigate the complexities of AI implementation more effectively and mitigate resistance. The success of AI in business depends not only on selecting the appropriate technology but also on ensuring a frictionless deployment process.

The steps of change management

Change management extends beyond the deployment phase, as it aims to ensure that employees at all levels recognise the value of the AI solution and perceive it as a long-term tool for enhancing their efficiency in the workplace.

In her study, “Creating a holistic change management method for Artificial Intelligence implementation in business processes,” Steffan Hakkers investigates the requirements of a holistic change management method to implement AI. The requirements she identified are: AI vision, process identification, continuous feedback, AI leadership and AI governance.

How to implement AI with change management processes

To achieve AI success, it can help to start with the following steps:

Start with a vision: It is important to start with a clear vision that aligns with strategic goals and delivers value. Assess your current capabilities, define desired outcomes and create a roadmap for your AI journey. Implement a pilot programme to generate quick wins and engage early adopters as champions for change.
Take a human-centred approach: Focus on solving problems and benefiting people rather than getting caught up in flashy technology. Involve both technical and non-technical stakeholders throughout the design and development process to ensure the AI solution meets the respective needs.
Empower staff: Address their questions and concerns through proactive knowledge sharing. Educate employees about how AI works.
AI literacy: An AI literacy programme should provide employees with the necessary skills and knowledge to effectively utilise AI technologies and applications in their jobs. Terms like automation, algorithms and machine learning can be intimidating, and it’s important to ensure that all team members have a clear understanding of AI basics.
Be realistic and responsive: When educating and promoting the adoption of AI, it is important to effectively manage expectations. If people have overly high expectations and AI tools do not meet them, employees may be less inclined to use such tools and leaders may be hesitant to invest in AI in the future.
Uncover roadblocks before launch: Introducing a new tool or technology is seldom a straightforward endeavour. It involves integrating the software with existing systems, providing training to users and implementing updated processes.
Build an AI community: To ensure the success of AI-related changes, fostering human connections is crucial. Building a community throughout the process, from introduction to deployment, accelerates understanding, strengthens adoption and instills a shared responsibility.
Encourage early adopters and praise every improvement: Having advocates who embrace the change and praising early wins creates momentum and encourages others to follow.

Al creates change that leaders must learn to manage

According to a recent Gartner study, AI is predicted to be the most disruptive technology in coming years, significantly influencing business models as it becomes ever more ubiquitous. To effectively harness the benefits of AI without harming employee engagement and morale, it is crucial for leadership to prioritise strong change management practices throughout the process. The change is coming; that’s inevitable, but what’s still under business leaders’ control is how they and their organisations react and respond.

The author, Prof Mark Nasila, is chief data and analytics officer in FNB chief risk office
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