Pinpointing AI Friction: Why Companies are Failing to Adapt to AI

In the past few years, artificial intelligence (AI) has become increasingly involved in people’s everyday lives – and businesses are no exception.

About 97% of business owners believe ChatGPT will help their business somehow. They’re adopting it at staggering rates and expect it to be a game changer, but most don’t know exactly why they need AI or how to use it – they just feel the pressure to use it like everyone else does.

This mentality is likely thanks to viral posts on social media networks, news stories, and anecdotes from thought leaders mentioning how the latest ChatGPT or other AI models are transforming industries, revolutionizing workflows, and allowing businesses to grow at exceptional rates.

With these incredible results seemingly everywhere, it’s easy to catch FOMO and get caught up in the hype surrounding automation and smart business tools.

Unfortunately, the reality is that AI isn’t a plug-and-play solution that instantly unlocks a business’s potential. It comes with costs, obstacles, and responsibilities that need addressing before the benefits become visible.

Many companies struggle to become AI-ready and adapt to AI effectively enough to reach this point. But why is it so difficult to use AI to its full potential? It creates change, like new responsibilities, processes, and tools to learn, that generate friction and make it difficult to complete tasks.

Keep reading to learn more about the impact integrating AI has on a business, where AI creates friction, and how to make AI a tool instead of a solution.

AI Impacts Most Parts of Business, But None More Than Employees

There aren’t many areas where a business can’t use AI. It works quickly and sometimes autonomously, making it effective for both customer-facing roles like customer service or social media management and backend data-focused processes like fraud management or accounting. 

However, AI integration isn’t something that can be rolled out successfully without a plan. AI needs to be property integrated into new or existing process to drive results. This means the tools and systems involved must be effective, and employees need to know how to use them.

According to Forbes, 56% of businesses use AI for customer service, making it the most common use case. Artificial intelligence thrives in this role, allowing businesses to answer FAQs quickly through instant messages, draft context-aware emails and other messages, and summarize issues to save agents time resolving them.

However, customer service is a highly involved role that relies on human understanding and problem-solving skills that AI can’t always replicate effectively. AI also relies on existing training content to answer questions, restricting its ability to provide valuable insight and making it prone to mistakes when it doesn’t have the right info available. As a result, a person must be available to review and quality-check its responses. 

This means customer service agents need to know how to work alongside AI tools and systems to be effective. If they don’t, efficiency suffers, productivity falls, and AI transformation efforts fall flat. And the same is true for any other role that uses AI.

AI is only as effective as a business and its employees make it – and that’s when it becomes difficult to use effectively.

AI Can Easily Create More Problems Than Solutions

Adding AI to workflows and processes creates change. 

It affects:

• How employees perceive their roles
• The steps they take to do their jobs
• Their tools
• Their overall productivity 
• How a business operates

And change can lead to problems with friction.

From the people to the technology to moral and legal implications, AI can complicate a lot about a business. And those complications cost money and impact outcomes that can make AI integration a net negative.

Employees Can Make Or Break AI Integration

Despite being a tech-based concept, artificial intelligence for businesses relies heavily on people.

Employees need to adopt the new tools and processes associated with adding artificial intelligence to their jobs. But not everyone is on board with AI in the workplace – especially if they think it’s going to replace them.

As many as 36% of Americans fear that they will be replaced by AI in the next five years, and 57% expect their jobs to at least be changed as a result of it. 

This concern over job stability and potential hesitation about whether they’ll be able to meet their current or future quotas can make it hard to get employees to commit to learning how to leverage AI.

Workers also need to adapt to the changes in their day-to-day work caused by AI. 

Artificial intelligence tools are inherently higher-tech than many other systems, and their processes can become more complex as a result. For example, customer service agents may need to use AI to reference a knowledge base, fact-check the answer, and use AI to write it in their brand voice instead of answering based on their own knowledge.

Unfortunately, some employees struggle with understanding this technology, reducing their productivity until they figure things out.

Updating Existing Systems and Integrating AI Is Costly

Implementing AI often requires specific systems, tools, and infrastructure that can become both time-consuming and expensive, such as new data management and processing tools to store data for AI models or hardware to handle the increase in processing demand associated with using AI.

Legacy systems may not have the storage or processing capacity needed to handle large amounts of data effectively.

Instead, it might require new hardware or software that’s built specifically for use with AI, like custom model frameworks that allow businesses to train and develop new AI tools. 

Integrating advanced AI systems may also require assistance from an AI transformation specialist who can ensure every tool is compatible. Or, it could take extensive training to help employees get comfortable with their new resources. 

Plus, converting to new systems and training employees often leads to service disruptions that reduce productivity temporarily, increasing costs and lowering revenue as these integrations begin.

All of these factors contribute to a high cost for integrating AI, which may lead businesses to abandon changes before they’re complete or spend more than they intended, reducing the risk-reward ratio.

AI Brings Up Security and Privacy Concerns

AI relies heavily on data, including some sensitive data, that adds another layer of responsibility to using it. Training a model often requires internal resources, customer communication logs, and other data to help the tool understand its purpose and create effective replies.

Using an external AI model to process any kind of sensitive information exposes customer or business data to breaches, unauthorized access, and hacks that violate privacy and affect data security. Because these tools aren’t controlled internally and exist on cloud servers, they’re at a higher risk of problems occurring. 

Internal AI models also require enhanced data security and data handling to prevent unauthorized use and avoid legal repercussions. Businesses can’t simply use the data that customers provide their chatbot or through app or website usage without the user’s permission.

Data must be encrypted through transmission between apps and in storage, especially in sensitive medical or legal use cases where additional laws and regulations need to be considered. There should also be access controls and monitoring to avoid unauthorized access to sensitive data and protect data integrity. 

Adapting to AI Relies on Preparation and Problem Solving

Solving the challenges and other friction caused by AI is essential for the success of AI integration. 

Resolving friction improves productivity by increasing adoption, making workers more efficient, and reducing the time it takes to adapt to new AI-related systems and processes.

Fortunately, with the right preparation and strategy, it’s possible to transition to AI-assisted operations and adapt to the changes AI brings in real-time.

Get Workers on the Same Page About AI’s Role

If workers don’t want to embrace AI as part of their work, it’s incredibly difficult to implement it successfully. In many cases, this comes from concern about how AI will impact their role, pay, and future as employees.

To calm these concerns, managers and team leads should communicate why the business wants to use AI, what its role will be, and how it will impact employees’ duties.

It’s important to highlight that AI is a tool to help enable workers to become more efficient and productive, not a replacement. People are essential for most business roles and even those that can be automated benefit from human oversight.

Set a clear and firm stance that AI won’t replace employees and provide guidelines to help explain the supportive role it will take. Then, communicate with employees throughout their adoption to help them see the value it offers so the idea of AI becomes less intimidating and they’re more comfortable embracing it.

Invest in Training So Employees Can Use AI Effectively Instead of Overcoming It

In most industries, the majority of employees will be new to artificial intelligence concepts, tools, and processes. The transition to these tech-focused changes can become overwhelming, reducing employee confidence and performance.

For workers to use AI effectively, they’ll need training and guidance that ensures they’re as efficient, accurate, and productive as possible.

Training should include:

• Explaining basic AI concepts to help understand how they work
• Introducing the specific tools and systems leveraging AI
• Hands-on training and live demonstrations
• Providing FAQs and guides
• Offering access to continuous learning and additional support

Training should also be part of an ongoing strategy, not just offered during the initial integration process. AI technology changes quickly and new ways to use it can appear as more workers use the tool, so training and other assistance provides the most up-to-date resources and tips to help them utilize AI to its fullest potential.

Monitor and Measure AI’s Impact on Employees’ Work to Address Friction As It Appears

Friction can occur as part of any significant business change, but it’s especially common because of the technical complexity associated with artificial intelligence. So, it’s important to continuously monitor the impact that AI has on business operations.

The best way to measure and evaluate the progress made in integrating AI is to ask those who will most need to use it: employees.

Employee surveys allow businesses to collect feedback on critical tasks and operations by asking workers how much work it takes to perform them. 

But it takes time to break this information down manually. Instead, remain adaptable and agile while implementing AI with a tool like FOUNT that visualizes the feedback and provides clear, actionable insights to tell whether AI is contributing to a productive environment.

If the results are poor, decision-makers can reevaluate the AI tools or processes being used to perform that specific task to see if there are ways to make employees’ work easier. Or, the results can point to employees requiring more training so they can effectively utilize AI to improve productivity and efficiency.

Using surveys before integrating AI also helps evaluate whether introducing AI actually makes work easier for employees or complicates it. This insight helps to guide future plans for AI integration and other forms of digital transformation throughout the business.

Looking Forward: The Future of AI

AI is progressively becoming more involved in businesses of all types and sizes – and it’s only going to become more important.

Forbes projects AI to see an annual growth rate of 37.3% over the next six years, which means it will become more critical than ever to become AI-capable and able to adapt to changing technology. 

Keep in mind that integrating AI isn’t easy. It takes an organization-wide commitment, a significant investment, and adaptability to overcome any friction that results from AI-related changes.

As technology advances, the potential benefits will only grow.