According to the PEX Network’s State of the Industry Report 2024/25, 47% of companies are currently investing in artificial intelligence to drive operational excellence (OPEX) and transformation.
In customer service and support, this means not only using AI reactively to respond to customer complaints but also using it proactively to anticipate future concerns or workflow issues based on historical data.
But if AI is already so widely available, what’s stopping organizations from embedding it into their customer service workflows?
It turns out there are a few barriers that prevent organizations from using AI to the fullest in this way. Read on to learn about those challenges — and if you find yourself in a similar situation, ways to make AI a standard component of your customer service workflows.
Three challenges organizations face when implementing AI to drive operational excellence
While AI has many use cases and benefits for organizations looking to drive operational excellence in customer service and support, your company may face a few hurdles before getting it right.
Prior to implementing AI-enhanced workflows, address any potential concerns head-on with your team. Here are the three we hear about most often:
- Poor data hygiene
It’s not uncommon for businesses to jump into AI adoption, only to find that the results fall short of expectations. The culprit? Disorganized, inaccurate, or outdated data.
AI relies on data to learn, make decisions, and automate workflows. But if the data your AI is trained on is flawed or incomplete, the outcomes won’t be reliable or effective.
“Your company’s data has to be in good shape so AI can parse it,” says Jay Tomlin, Senior Director of Product Management at Nintex. “Step one is ensuring the data is well-structured, clean, accurate, and accessible to any AI bots or knowledge agents.”
This means having organized systems to store your data and regularly replacing any outdated information. Without this foundation, AI can’t identify the patterns or insights needed to optimize processes, improve efficiency, or make meaningful decisions.
- Unpredictable costs
It might sound tempting to try to handle AI implementation in-house. Companies often think they can save money by skipping that extra line item on their purchase order. But in reality, doing it all on your own can actually end up costing more.
Tomlin says that using large language models (LLMs) directly can be cost-prohibitive, especially if you have to pay every time someone from your org uses them. “This is one area where Nintex can really help,” he says. “A lot of AI features are built right into our platform.”
Rather than having to “pay as you go” or develop and integrate AI features from scratch, you can access sophisticated features with an AI-powered platform that integrates with your systems and workflows. This allows you to cut costs and serve your customers better.
- Nervousness around sharing sensitive data
Companies often hesitate to give AI access to personally identifiable information (PII). That’s completely understandable — after all, it can be hard to comprehend exactly how your information is used, logged, or stored.
“If you choose to use an AI engine, you need to carefully consider what data is appropriate to share and what questions are safe to ask, as that information often goes to the cloud,” Tomlin says. “Customers are right to be cautious about who might have visibility into that data.”
However, avoiding AI altogether isn’t the best solution. Instead, get clarity on what data you feel comfortable sharing and stick to those guidelines. By defining your company’s boundaries and choosing AI systems that can handle sensitive data securely, you balance the benefits of AI with peace of mind.
For example, Nintex ensures that PII is never used for AI training or stored in the cloud in a way that could expose it to unauthorized access. Knowing that these protections are in place offer peace of mind about using AI-powered platforms — and provide reassurance to your customers, too.
How to standardize predictive workflows using Nintex
If any of the above challenges resonate with you, onboarding an automation platform with integrated AI can help mitigate or remove these barriers — and help you successfully scale AI integration in your customer support functions.
If you use Nintex Process Manager, you’ll follow a three-step approach to standardize your workflows: document your workflows, build the automations, and optimize your processes.
1. Use Nintex to capture your workflows
When improving your workflows, you don’t need to automate everything at once. The best approach is to start by examining and documenting your current processes.
“One of our key capabilities is Process Capture, which leverages AI to document existing workflows,” Tomlin says. “For example, you can record a user’s screen as they perform a process and use AI to convert those visuals into a detailed, documented procedure that others can follow.”
This process capture feature lets you visualize and standardize even the most complex workflows. By using AI to record and break down the steps, you create a clear process that’s easy to automate and improve.
2. Let AI determine what can be automated
If you capture hundreds of processes, it might feel overwhelming to figure out where to start with automation.
This is another area where AI can be a powerful productivity driver for your organization.
“Once the process is documented and you have a clear understanding of the ‘as-is’, AI can further analyze it to identify tasks that could be automated,” says Tomlin. “This includes determining which repetitive tasks currently handled by humans could be performed by machines to improve efficiency and predictability.”
For example, if you’re using Nintex, you have access to Cloud Automation, which can interact with customer relationship management (CRM) platforms like Salesforce, enterprise resource planning (ERP) tools like SAP, and a variety of onboarding tools for human resources. Cloud Automation lets you automate manual data-entry tasks by reading and writing changes across systems — a huge time-saver for your team.
Nintex also offers another powerful tool: robotic process automation (RPA). This technology mimics human actions by actually driving a mouse or keyboard to perform repetitive tasks, such as selecting between apps or entering data — saving your employees time and increasing their efficiency.
3. Continue to optimize workflows as needed
As AI learns your team’s behaviors over time, it can make recommendations on what to automate or optimize next. This ongoing optimization keeps processes efficient and relevant as your organization scales and customer needs change.
“Once your automations and solutions are built, we also want to use AI and machine learning to optimize and keep improving,” says Tomlin. “It’s like a continuous virtuous cycle of making a change, monitoring, and measuring the improvement, and then using those learnings to make another, better change.”
In other words, Nintex isn’t a “set it and forget it” type of tool, but a true partner in optimization and automation. You can actually build predictive workflows — AI-powered systems that not only automate current tasks but also predict and adapt to future needs.
In Nintex Process Manager’s centralized process repository, your processes are documented in natural language and grouped by function — say, tasks for customer service agents or managers conducting employee reviews.
From this library, Nintex helps you find new opportunities for improvement or automation. For example, if a process involves repetitive tasks on a computer, you might get an alert with a recommendation for RPA. Or if a process includes manually entering data into Salesforce, a form or workflow could help automate that input.
“Having a human review hundreds or thousands of documented processes to identify automation opportunities would take forever—especially since these processes are always evolving. Instead, AI can analyze the language in these procedures, identify repetitive tasks, and suggest automations. This approach helps Nintex empower organizations to optimize their workflows efficiently.”
—Jay Tomlin, Senior Director of Product Management at Nintex
Three ways to leverage AI in customer service and support
29% of customer service and call centers are already leveraging AI, making it the technology’s second biggest use case, just behind operations. As more companies adopt AI, its potential to improve efficiency, reduce costs, and enhance customer experiences becomes increasingly clear.
Here are three ways modern organizations can use AI technology to hone their customer support strategies, streamline their operations, and stay ahead of the curve:
- Interactive voice response systems (IVRs): These systems promote self-service by removing the need for human intervention. The technology can understand customer questions, like “What’s my balance?” or “Where’s my order?” This allows your customers to get fast and friendly support without the hassle of being passed from person to person — and saves your employees time and boosts their efficiency.
- Integrations with chatbots and record systems: By connecting to these systems, AI helps automate repetitive tasks, retrieve customer information, and surface real-time data. Not only does this free up time for humans to focus on more complex issues, but it also ensures a smoother workflow across departments.
- Anticipate needs and identify emerging customer service trends: By analyzing data patterns in customer behavior, AI helps you predict potential issues. For example, it might identify spikes in product returns or a large number of users struggling with a software feature. That way, you’re not just responding to customers’ needs as they arise — you’re staying one step ahead, making customer service more efficient, personalized, and responsive.
Work smarter with automation and predictive AI
Paradoxically, offering your customers the human support they want from your organization gets much easier when you’ve integrated AI support in the right places. And for customer service and support operations, staying competitive means embracing AI and automation in your workflows. An AI-powered automation tool like Nintex helps you work toward operational excellence while overcoming some of the major challenges you’d otherwise face, like disorganized data, unpredictable costs, or security concerns.
With Nintex, you can capture your processes and get AI-powered input on how to optimize them — all in one easy-to-use platform. Reach out for a live demo to see Nintex in action.
