The pace of change escalated rapidly during Covid. But it was building altitude well before that. Just as we all went into lock down, our data scientists and analysts were already talking enthusiastically about artificial intelligence (AI) and machine learning, and the potential applications these amazing tools could have. Then amidst fears of viral contagion, suddenly we saw a world leaning into technology solutions that replaced human interactions with a passion.
Prior to Covid, conversations were about big data, open data and data security. Anonymising mass amounts of large data was the key issue, so that specific or sensitive information belonging to individuals could in no way be reconstructed from all the breadcrumbs when big data was opened up to outside users. From these innovations we saw public transport apps that predict how late and how full the bus is going to be, and we saw strides forward in wearable devices that previously counted steps, and now can take an ECG which you can seamlessly email to your Doctor.
Progressively our Data and Analytics and Information Technology Departments tackled the safety and security issues, and we saw more data-enriched tools moving on to the desktops of ordinary employees doing routine operations. Organisations are enhancing the customer experience with AI-powered chatbots and virtual assistants, providing personalised recommendations, and offering 24/7 support. They're also using AI very commonly to detect anomalies, identify potential threats, and protect against cyberattacks. The integration of artificial intelligence and the adoption of digital technologies has moved well into the mainstream where they are now essential for businesses to stay competitive.
However, implementing these technologies successfully requires more than just hooking up a data source to a front-end app. It requires effective change management strategies to support the organisation through the transition. In fact, the implementation of AI tools is a classic example of how change management plays a critical role in facilitating people to adopt new ways of working. Let's have a look at understanding change management's vital role in supporting AI and digital adoption, driving agile transformation within organisations.
Embracing Digital Transformation Through Change Management
Change management serves as a guiding light for organisations undergoing digital transformation. By understanding the intricacies of organisational change and human behaviour, change management professionals can support seamless transitions from traditional to digital processes. The structured approach offered by change management ensures that all stakeholders are on board, mitigating resistance and fostering a culture of adaptability.
From the Research
When it comes to adopting artificial intelligence, several challenges and points of resistance have been identified in the emerging research.
Lack of Knowledge and Expertise: Many organisations struggle due to insufficient understanding of AI’s strengths and weaknesses. Investing in AI education for teams is crucial to overcome this challenge.
Data Privacy and Security Concerns: Organisations worry about data protection and privacy when implementing AI systems. Ensuring robust impact analysis of digital processing solutions will identify where upgraded security measures are essential.
Cost of Implementation: Deploying AI can be expensive, including infrastructure, training, and maintenance costs. Budget considerations often hinder adoption and projects can therefore fall slightly short of making use of the rich resource of data that is sitting un-mined in the organisation's systems.
Resistance to Change: Employees very often feel intimidated by AI, fearing automation will replace their roles. Overcoming this resistance requires effective communication and change management.
Ethical and Legal Considerations: Organisations must navigate ethical dilemmas related to AI, such as bias, fairness, and transparency. Conducting a solid change impact analysis on the relevant policy layer will provide a roadmap to good governance of AI and digital tools.
Understanding and addressing these challenges with a sound change management strategy can lead to successful AI deployment in businesses.
Nurturing a Culture of Adaptability
Let's dive under the covers of resistance to change. Employees feel overwhelmed by the new tools and processes, leading to decreased productivity and morale. They feel worried that if they help a machine to learn from them, that machine will learn their entire job, and eventually replace them. They are concerned that they're providing valuable intellectual property to organisations only to result in the risk of making their expertise redundant.
Organisations must determine their AI strategy. In particular, whether an AI implementation is intended to replace human jobs. If so, organisations must get this messaging clear and communicate it well - whether good news for jobs, bad news for jobs, or a test and learn approach that sits somewhere in the middle. An employee needs to be able to trust the organisation's AI agenda before they will trust the individual AI tools.
The Employee Experience
When introduced to AI tools for the first time, an employee may experience a range of things. While they might be curious about the tool's capabilities, there can also be apprehension. We know from research that employees are already wondering how AI will impact their work, job security, and daily tasks. Assuming the employee is willing to engage with an initial learning curve, they may start by exploring the AI interface or software. They learn how to interact with it, input data, and interpret the results. This phase involves trial and error, as well as seeking guidance from colleagues or training materials. As they gain proficiency, they start experiencing the benefits.
AI can automate repetitive tasks, provide data-driven insights, and enhance decision-making. This realisation often leads to a sense of delight and empowerment. But despite the benefits, challenges usually arise. The employee may encounter unexpected errors, biases, or limitations. Debugging AI models or adjusting input parameters can be frustrating, especially if it disrupts their workflow.
This experience may interrupt their enthusiasm, but over time, employees can adapt to using technologies accurately and safely, as long as they don't stop trying. By encouraging employees to integrate AI usage into an existing routine, they can learn to leverage its strengths while mitigating its weaknesses. This adaptation involves building trust in AI’s recommendations and understanding its boundaries. This is when organisations see employees begin to collaborate with AI systems.
Following a successful digital adoption or transformation, employees appreciate how AI augments their abilities, providing insights they couldn’t achieve manually. This collaboration becomes a valuable asset in their work.
The experience of using AI for the first time combines curiosity, learning, challenges, and eventual integration. Supporting this experience with change management activities will help ensure employees move through each phase of discovery and adaptation so that the organisation's investment in the AI tool is protected as benefits are realised. Change management fosters that culture of adaptability and resilience by involving employees in the change process, providing training and support, emphasising the benefits of digital adoption, and bridging the gap between old and new ways of working.
Aligning Strategies for Success
Successful digital adoption relies on the alignment of business strategies with technological capabilities. Change management professionals work hand in hand with leadership teams to ensure that the organisation's goals are in sync with its AI and digital initiatives; and that this connection is communicated clearly to the change audience. By developing clear communication channels, setting realistic expectations, and establishing measurable goals, change management ensures that the organisation is poised for success in its digital transformation initiatives.
Agile Approaches for Dynamic Environments
For organisations already maturing in agile project management, or that generally value pivoting quickly towards market and technology changes, agility in change management is key to a competitive response. Change management supports AI and digital adoption through both implementing and utilising agile methodologies that allow organisations to adapt quickly to changing market conditions. By breaking down complex projects into manageable tasks, fostering collaboration among teams, and iterating based on feedback, change management enables organisations to navigate the uncertainties of digital transformation with confidence.
Change management, AI and Digital Adoption
Change management is a key lynchpin that holds together the people lens on the intricate web of AI and digital adoption within organisations. By providing structure, fostering adaptability, aligning strategies, and promoting agility, change management plays a crucial role in driving successful transformations. As businesses continue to embrace digital technologies and AI, integrating change management practices will be essential to ensure that businesses can create a smooth continuum of innovation, transition and benefit realisation. Change management professionals are well placed with the knowledge and processes needed to help organisations navigate the complexities of digital adoption.
Agencia Change has multiple offerings to help organisations get to grips with AI. For more information, have a look at https://www.agenciachange.com/business-solutions or choose an AI workshop to conduct with your team:
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