Research Hub > CDW Leverages AI To Drive Innovation and Enhance Customer Experience

February 21, 2025

Case Study
7 min

CDW Leverages AI To Drive Innovation and Enhance Customer Experience

By harnessing artificial intelligence to increase efficiency and deliver value to customers, CDW sets a standard for responsible and strategic adoption across four key areas: employee productivity, SaaS integration, IT support and digital sales.

With 15,000 coworkers, 250,000 customers and more than 1,000 technology partners, CDW serves as a robust proving ground for artificial intelligence. By implementing AI within its own operations, CDW not only improves internal processes but also develops expertise that enables it to guide customers on their AI journeys.

“Given that we are in the industry, it’s important for us to be an AI leader — to do something innovative and then be able to demonstrate our capabilities to our customers to show that we are not just talking about AI, we’re actually doing something with AI,” says Anurag Batra, CDW’s head of enterprise architecture.

When CDW embarked on an ambitious digital transformation in 2020, AI was a cornerstone of the company’s strategy. CDW adopted a three-pronged approach, says CTO Sanjay Sood: integrating off-the-shelf capabilities, developing custom solutions for specific workflows, and creating in-house tools and customer experiences using deep learning and large language models. With the rise of generative AI in 2023, CDW expanded its efforts by identifying new use cases, establishing policies and procedures to ensure coworkers use AI responsibly, and helping coworkers increase their AI fluency.

“Internally, we’ve built these capabilities and we’re proving the technology of the business,” says Sood. “We’re constantly working with the business on how to actually adopt and maximize the value of this new technology.”

Key AI Growth Areas at CDW

CDW’s internal AI initiatives are grounded in four areas: enhancing employee productivity, using AI capabilities as they emerge in Software as a Service (SaaS) platforms, streamlining IT processes, and supporting digital sales and customer experience initiatives. By refining these capabilities, CDW continues to evolve its AI strategy while gaining valuable insights from experimentation.

One of CDW’s early projects involved deploying Microsoft Copilot to 10,000 coworkers. The rollout included targeted training sessions to help employees understand how to use AI tools effectively and to create communities of practice that could share best practices for various departments, says Sood.

Another priority is expanding AI capabilities within CDW’s SaaS ecosystem, including platforms such as Salesforce, ServiceNow and Workday.

“The major vendors have robust roadmaps for integrating AI capability into those platforms,” says Sood. “One of the benefits we always anticipated is that we could ride the coattails of these large tech firms investing in AI. Given how big of a partner we are, we often get early access to these capabilities.”

“We’re constantly working with the business on how to actually adopt and maximize the value of this new technology.”

— Sanjay Sood, CTO, CDW

Leveraging AI for IT is another focus area, one that aligns with CDW’s digital transformation goal of making IT more proactive and strategic. For example, coding teams use generative AI tools such as GitHub Copilot to increase productivity and improve the quality of code and documentation in software development.

CDW has also achieved significant success with HAROLD, an IT support chatbot launched in 2021. Housed in Microsoft Teams, the bot resolved more than 42,000 issues for nearly 13,000 coworkers in 2023 — essentially managing 40% of support tickets.

In addition, AI is powering cybersecurity use cases, such as summarizing vendors’ release notes to understand how software updates could affect the company’s security posture.

“That helps us not only scale our threat detection capabilities but also understand where the biggest threats may be from an external perspective,” Sood says.

Finally, CDW has developed bespoke AI tools for digital seller and digital customer applications; for example, integrating AI into its digital platforms to empower sellers with information that best supports customers.

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Strategic Selection and Implementation of AI Use Cases

At CDW, use cases are carefully selected to ensure that AI initiatives align with strategic goals. Corporate Strategy Director Justin Jones highlights the company’s practical approach to identifying high-impact use cases. In 2023, CDW used hackathons and the Microsoft Viva Engage platform to gather AI ideas from employees, narrowing down to 120 concepts and ultimately prioritizing 10% for immediate exploration.

One promising use case: automating responses for request-for-proposal documents. Currently, each RFP response takes about 40 hours to prepare. As a result, CDW lacks the bandwidth to pursue all qualified RFPs.

Batra and a colleague developed an AI tool that searches a data repository of previous RFP responses and generates answers to evergreen questions, such as describing CDW’s experience in a particular industry. The initial proof of concept reduced drafting time by 23%, and the pilot netted a 37% reduction, based on feedback provided by the test users, says Batra. The team is evaluating an expansion of this homegrown tool, as well as onboarding potential third-party AI solutions to build on these improvements.

“My hunch is that once we go into production, it’s going to be a lot bigger,” he says. “It’s a lot easier to tweak an existing essay than to write an essay.”

On CDW.com, CDW recently launched a fully automated customer service bot that lets customers ask questions about policies, orders and so forth. A pilot for the next phase, where the bot will provide personalized feedback and handle customers’ requests, is underway.

“It has essentially learned our internal processes and procedures, and through a natural-language chat interface, it can interact with our customers,” says Sood. “We’re learning a ton by getting hundreds of conversations a day and seeing all of the ways this technology can help.”

In another customer-facing use case, conversational search will help CDW.com users find the right products and services quickly. For example, if a customer is looking for a laptop, the bot might ask, “Do you travel often? Do you use peripherals? Do you frequently use your laptop on battery?” Armed with the answers, the bot can then direct the customer to the most relevant results.

“It’s a better and more natural way of interacting with a very large, complex catalog of products,” says Sood.

To support internal teams, CDW has developed several “knowledge bots” that digest large quantities of information — white papers, procedure manuals and other documents — and put that knowledge to work through a conversational interface.

AMANDA is a digital assistant that automates account managers’ routine tasks and equips them with information to better support customers. For example, if a customer needs a security solution, an account manager would typically consult with one of CDW’s technical experts to guide the customer to the right solution. AMANDA equips sellers with some of those questions and insights up front, allowing for a more efficient conversation.

Meanwhile, says Sood, the IT bot HAROLD continues to get smarter. In mid-2024, CDW launched a new HR platform to 15,000 coworkers and trained HAROLD to provide Tier 1 support for the release. HAROLD’s next assignment will be answering users’ questions during a major release CDW is launching in Fastlane, the application automation platform.

“Instead of being purely an IT tool, HAROLD is now assisting us with change management communications across the organization for high-profile projects,” says Sood.

40%

The percentage of IT support tickets closed by HAROLD, CDW’s AI-driven chatbot, in 2023

Source: CDW


Refining a New RFP Process

Aligning artificial intelligence with business needs requires detailed, honest feedback from users, says Anurag Batra, CDW’s head of enterprise architecture. While developing the AI capability to draft RFP responses, feedback was crucial for iterating effectively and guiding the AI toward a nuanced output.

“Even if it’s 80% right, we want to understand the 20% that does not work,” says Batra. “It’s a model, so you need to continue refreshing the data, updating the model and adding continuous feedback to improve the relevancy.”

Continuous data hygiene is essential to ensure the data repository returns the desired results.

“You need a process to keep refreshing the data and deleting what is not relevant so it doesn’t impact the response,” Batra says.

He also observes that AI projects require users to become AI-savvy and to understand their role in the new process. For instance, they need to recognize that if an output isn’t correct, that doesn’t mean the AI is deficient; rather, it likely means that the input data was incorrect.

“That’s a mental shift that needs to happen,” says Batra.

Refining a New RFP Process

Aligning artificial intelligence with business needs requires detailed, honest feedback from users, says Anurag Batra, CDW’s head of enterprise architecture. While developing the AI capability to draft RFP responses, feedback was crucial for iterating effectively and guiding the AI toward a nuanced output.

“Even if it’s 80% right, we want to understand the 20% that does not work,” says Batra. “It’s a model, so you need to continue refreshing the data, updating the model and adding continuous feedback to improve the relevancy.”

Continuous data hygiene is essential to ensure the data repository returns the desired results.

“You need a process to keep refreshing the data and deleting what is not relevant so it doesn’t impact the response,” Batra says.

He also observes that AI projects require users to become AI-savvy and to understand their role in the new process. For instance, they need to recognize that if an output isn’t correct, that doesn’t mean the AI is deficient; rather, it likely means that the input data was incorrect.

“That’s a mental shift that needs to happen,” says Batra.

Achieving Value Through Business-Led Strategies

A key principle of CDW’s AI adoption approach is that such efforts are technology-enabled but must be business-led.

“As we think about driving value and seeing real impact, the key is business ownership and accountability in rolling these out at scale,” says Jones. “This means defining and tracking outcome-based metrics to evaluate the efficacy of a given solution.”

AI is a two-sided coin, says Sood: Organizations must understand how to leverage AI technology to solve business problems, and they must position business leaders to drive adoption and change management. This approach is evident as CDW continues to integrate AI into the RFP process.

“Stakeholder engagement, change management and process definition — those are three areas we should focus on before we start any conversation,” Batra says.

That’s important, in part, because AI is costly to implement and experiment with, says Sood.

“The business needs to understand what the value is, how to quantify the value and what has to change in business functions to maximize that value,” he says. “Otherwise, you’re going to continue to grow the cost of technology without realizing the benefit on the other side.”

Amy Burroughs

Writer
Amy Burroughs is an award-winning writer specializing in journalism, content marketing and business communications.