6 Change Management Strategies To Avoid Enterprise AI Adoption Pitfalls

September 3, 2024
AI Adoption cover image.

One of the biggest reasons enterprise AI software fails has nothing to do with the software development. The lack of change management can cause your AI adoption to fail no matter how much potential the solution has to positively impact the organization.

Many tech leaders have more of a blind spot than they realize when it comes to change management and overestimate their ability to manage change. According to a Gartner study, 74% of leaders say they involve employees in change management, but only 42% of employees say they were included.

Implementation of AI is inherently a disruptive endeavor that requires a specific focus on change management. Organizations that create a change strategy as part of their enterprise AI adoption will see greater success. In fact, enterprises that integrate change management are 47% more likely to meet their objectives.

If you’re looking to avoid this AI fail, learn how to navigate the challenges of AI adoption and set your organization up for long-term success. Over the past decade of AI software development, Gigster has developed proven strategies to manage the transition, align stakeholders, and foster a culture of innovation, ensuring your AI initiatives deliver maximum value with minimal disruption.

Understand the Impact of AI on the Organization

Artificial intelligence has the potential to disrupt workflows, roles, and responsibilities. Unfortunately, thanks to the rise in AI technology like ChatGPT, many leaders are looking to “do AI” without fully understanding how it will impact the organization or what benefits you may see.

Before your enterprise adopts AI, prioritize AI opportunities by choosing a single business function for AI transformation and aiming to transform 5-10% of the business. Focus on the AI projects that most align with your strategic priorities and long-term goals and match your current level of AI readiness.

Next, identify areas within the organization most affected by your proposed AI transformation. Starting with only 5-10% of the business will limit this impact and increase your chances for adoption. Assess the overall impact and make sure to communicate this impact to users, employees and stakeholders.

Align Stakeholders and Leadership

A recent study found 37% of executives underestimate the importance of change management and its impact through the transformation phase. Getting stakeholders invested in an artificial intelligence initiative and communicating the potential benefits and disruptions is key to seeing full adoption.

Make sure to engage stakeholders early to align their business objectives with the goals of the AI software development. This is also the opportunity to communicate the benefits of the project and address any concerns they might have about AI adoption.

Address Resistance to Artificial Intelligence Adoption

Reasons Employees are Resistant to Change

Image credit: Oak Engage.

In addition to stakeholder resistance, employees will be resistant to any change in the organization - especially related to AI. In 2023, only 43% of employees say their organization is good at managing change, compared to nearly 60% in 2019.

The past few years have been defined by rapid transformation and the introduction of new, disruptive technologies. Failing to effectively communicate these changes has resulted in fear of the unknown (38%), lack of awareness around the reason for change (39%), and general mistrust in the organization (41%).

Your change management plan needs to build trust through transparency, communication, and inclusion. Involve employees in the AI development and deployment process. This will provide valuable feedback that will make your AI tool more effective, help identify sources of resistance to AI, and give employees a sense of ownership that will increase the chances of adoption.

Create AI Training and Education Programs

There is a major skills gap in artificial intelligence that can hold some digital transformation back. Outsourcing AI software development allows you to benefit from AI without hiring a large, specialized development team. However, you’ll still need to equip your employees with AI-related skills to interface with new software and workflows.

Gigster worked with a large scale telecommunications company to create a machine learning solution to optimize customer service through their call center. Changing the workflow of a call center with thousands of employees can’t be expected to happen overnight. Changes within those teams needed to be planned far in advance and training and education programs developed for the different employees and job functions. The telecom company tailored education to different roles within the organization to give IT, call center employees, and managers the role-specific knowledge they needed to succeed with the new AI tools. Due to this change management strategy, the new ML solution was integrated successfully and the company was able to improve customer service across their call centers.

Monitor and Measure Successful AI Adoption

What does success look like for your AI adoption? Over half (51%) of managers and employees say leaders don’t outline clear success metrics when managing change. This is why 50% of leaders don’t know whether recent organizational changes have succeeded or not.

Set up specific metrics to track the success of AI initiatives and change management efforts. Be transparent about what metrics you are tracking and what success looks like. Regularly review and adjust your change management plan as you continue to collect data on the successful enterprise artificial intelligence adoption.

Develop an Artificial Intelligence Change Management Plan

Once you have determined the organizational impact of your AI project and collected input and potential resistance from employees and stakeholders, you can develop your AI change management plan. This should be a document that sets clear objectives, timelines, and metrics for success. It should also put the AI adoption into context for the organization’s broader goals and strategy. Here are key elements to include:

  • Strategic Alignment: Define the long-term goals of AI adoption and how it aligns with the organization's overall strategy.
  • Project Ownership: Identify the key stakeholders - both those championing the project and those who will be impacted - and outline their roles and expectations.
  • Impact Assessment: Include data on the organization’s current workflows and systems, current AI readiness, and how these will be impacted by the AI project.
  • Training and Development Plan: Identify current AI skills gap and create a training program to equip employees and leaders with necessary skills.
  • Communication and Feedback Protocols: Create systems for communicating changes as they are implemented and for receiving and responding to employee feedback throughout the process.
  • Metrics for Success: Define what a successful AI adoption will look like and how the success will be measured.

AI Development Services

Avoid the change management pitfalls. Let Gigster make the process simple and cost-effective with our AI development services.

If you’re looking to transform your organization with AI software development, Gigster can help. Our experts will help identify high-impact AI/ML use cases and determine the ideal AI platform configuration to meet your goals. We’ll work with you to integrate the solution into your existing workflow to avoid enterprise AI pitfalls and give your change management the best chance for success.

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