The Role of Change Management When Implementing AI

Artificial intelligence (AI) is changing the way we live and work. Machines capable of making complex decisions used to be relegated to science fiction books. Today, programs running AI can pull business insights from a spreadsheet full of data points, determine the most relevant news for the viewer, and take over tasks like data entry or matching invoices with purchase orders.

Businesses, in particular, are paying attention to the benefits of AI. By 2024, the AI market will be valued at an estimated $21 billion. Though adoption rates are growing, overall adoption remains relatively low. A Gartner survey reported that 37 per cent of organizations have implemented AI, which is an increase of 27 per cent in four years.

This represents a massive opportunity for organizations to streamline their operations and gain a competitive edge through the use of software with AI functionality.

AI Provides Companies with a Competitive Edge

AI technologies promise to help boost productivity, streamline data analytics, and make it easier and cheaper for businesses to deliver their products and services to the right customers.

However, realizing that potential requires deploying new technologies that have AI capabilities as widely as possible, which can be a hurdle, especially for global companies with hundreds of employees.

AI’s success in the business world relies not just on choosing the right technology, but also on ensuring deployment goes smoothly. This is why change management may be the key to successfully leveraging AI in the business world.

A Quick Definition of Change Management

Change management is a set of processes designed to help organizations and individuals successfully implement new initiatives, including launching new AI solutions and managing reorganizations. The goal of change management is to ensure the success of new initiatives by creating a comprehensive plan to launch and track the impact of new technologies.

The steps of change management in AI deployment may shift based on the solution and organization, but generally include:

• Obtaining buy-in from stakeholders

• Outlining who is responsible for completing specific tasks

• Implementing team training

• Ensuring high adoption rates

• Securing the long-term success of the new solution

Change management doesn’t end once the new system is deployed. It also ensures that employees at all levels understand the value of the AI solution and view it as a tool to help them work more efficiently in the long term.

How to Implement AI with Change Management Processes

To ensure investments in artificial intelligence pay off, organizations must pair AI deployments with change management. Otherwise, those investments may be underutilized, underfunded, and ultimately unsuccessful.

Here is how change management can improve the overall success of AI technology in the business world.

Define Training Initiatives

Training is crucial to any new business initiative’s success, but even more so for AI solutions. For workers unfamiliar with how AI functions in the workplace, the futuristic technology and terms may be intimidating. While terms such as automation, algorithm, and machine learning may have positive connotations for some, the basics of AI may not be as clear to other team members.

Businesses with the smoothest AI transitions start education early and tailor it to multiple stakeholder groups before launch. For example, a company deploying a sales platform with built-in AI would need to offer training to the sales team so they could understand sales automation, predictive lead scoring, and the insights reported by the platform that can help them win more opportunities.

Providing stakeholders with a baseline knowledge of the value of AI ensures teams have a clear understanding of the benefits of AI adoption and the new tool’s capabilities. Training should include everyone who will work closely with the new system.

Uncover Roadblocks Before Launch

Launching a new tool or piece of technology is rarely a simple process. The software must integrate with other systems already in place, users need training, and processes have to be updated and put into play.

Identifying potential problems early allows teams to develop tailored solutions to overcome those roadblocks before they become larger challenges.

The launch of new AI solutions can impact teams and systems beyond those most closely related to the process. Sales software with AI will clearly impact the day-to-day tasks of the sales team, but may also affect operations in other departments. For example, with a more accurate sales forecast because of AI’s machine learning capabilities, marketing may have to update their content schedule, inventory may drastically change, and seasonal staff may be needed to handle an influx of customers. Part of the change management process is considering the wider impact of the new technology on the business as a whole.

Another common roadblock to launching AI solutions is resistance from employees. They may feel the current system works well enough, worry their job may be automated, or not understand the true benefits of AI in their daily role. Change management processes predict and plan for these hurdles, leading to a faster, more successful launch — and more satisfied employees.

Other roadblocks that can be mitigated through change management may include verifying the true need for the solution, ensuring proper metrics tracking, and reducing critical system downtime. Recognizing barriers early in the process enables new processes to integrate as seamlessly as possible into existing processes.

Increase AI Adoption Rates

Adoption rates, or the number of people who actually use a new solution, should be one of the key metrics organizations track to ensure a new solution’s long-term success. However, too often organizations focus on other metrics, such as training attendance or the amount of data input.

When a company pours resources into deploying software with AI, but doesn’t provide proper training or develop a new reward system, it may not see the expected return on its investment. The goals of increased efficiency and productivity will falter when few people use the new system to its fullest.

For example, suppose a company invests in a new ecommerce platform that has built-in AI. The recommendation engine boosts sales of like and complementary items. Marketing needs to be involved in this part of the site so the team can tailor email marketing. Customer service should be consulted to help input data so the recommendation algorithm is helpful. If a team member sees a glitch in the algorithm, they should know who to speak to in order to increase accuracy. The company must offer training so employees don’t need to reach out to the help desk with questions, which could result in slower resolution times for other IT-related tasks.

The change management process tracks adoption rates and ensures new rewards and training are accessible to everyone in the organization who needs them.

Ensure the Long-Term Success of AI Technologies

Companies that implement AI solutions often see higher productivity, improved data accuracy, and reduced costs. However, the long-term success of AI technologies isn’t determined at the end of a day or even several weeks after launching.

New technologies can take time to implement and resistance is a common challenge in change management. Resistance can be particularly common when launching large-scale AI solutions that dramatically change the way some employees work.

One of the keys to successful AI adoption is sustaining the changes and embedding the new processes into an organization’s workflow and culture. This may include updating process guides, verifying new hires are appropriately trained, and ensuring that all employees understand the new technology’s immediate and long-term benefits. A change management process outlines these initiatives from the start, improving the new technology’s long-term success.

Conclusion

Artificial intelligence is changing the way we work, live, and learn. Purchasing and implementing a new solution with built-in AI can be an challenging and time-intensive task for organizations, which means successful implementation is crucial to the entire organization’s long-term success.

Change management provides a road map for AI implementation that guides your business through the change. It helps anticipate challenges and ensures companies reap the full benefits of AI technology.