How AI-Powered Virtual Assistants Will Transform Enterprises

It’s not enough for an AI assistant to answer questions; it also needs to interpret intent and optimize decision-making, he says.

AI assistants also require strong data integration capabilities to provide accurate, real-time insights. “If you don’t have the right data, you don’t have anything,” says Sheryl Kingstone, head of the software experiences group at 451 Research.

Kingstone explains how the most effective AI assistants must be trained on enterprise-specific data sets and have an advanced reasoning engine that dynamically determines “next best actions.”

Enterprise-grade AI assistants must also offer cross-platform compatibility and multimodal communication.

“Whether it’s text, voice or predictive analytics, the ability to work across multiple input channels and applications is what makes an AI assistant truly effective,” Kumar says.

Click the banner below to read the 2025 CDW AI Research Report.

How to Choose the Right AI Assistant

The process of selecting an AI assistant depends largely on an organization’s specific needs and the complexity of tasks it wants to automate.

“Understanding what process you’re trying to optimize is step one,” says Kingstone. “Do you want to build from scratch, or do you want to leverage prebuilt AI models from vendors?”

This approach varies by organization as some prefer end-to-end AI platforms from cloud providers, while others may opt for domain-specific solutions.

Cost is another key factor McKeon-White points out.  AI assistants operate on a wide range of pricing models, so IT leaders need to understand the price structure ahead of deployment.

“Some businesses use a consumption-based approach, and others opt for flat monthly fees.” Either way, the cost fluctuates “depending on how many services the AI model needs.”

Scalability is another major consideration as AI assistants need to evolve with the demands of the business. “Many enterprises start with AI assistants in customer support but then expand to HR automation, finance and supply chain optimization,” he says.

Different Use Cases for AI Assistants

Across industries, AI-powered virtual assistants are proving to be the most transformative in customer service, sales and operations.

“Organizations with high volumes of customer support tickets — think retail, manufacturing and finance — are seeing real success with AI assistants,” McKeon-White says. “Deflecting even 25% of 200,000 monthly support tickets leads to major cost savings.”

And the use cases continue to grow. AI assistants are also helping with sales and marketing.

“We’re seeing a rise in sales lead generation assistants that can qualify leads, respond to customer inquiries and even schedule meetings, freeing up sales reps to focus on closing deals,” Kingstone says.

In corporate settings, AI assistants are streamlining administrative processes. In healthcare, “providers are using AI assistants to handle appointment scheduling, medical billing inquiries and even diagnostic support,” Kumar says.

In the financial sector, AI assistants are transforming operations by automating fraud detection, assisting in compliance reporting and managing transaction workflows.

“Banks and insurance companies are using AI to optimize risk assessment models and handle regulatory inquiries more efficiently,” Kingstone says.

Privacy and Security Implications of AI Personal Assistants

While AI assistants get more work done, they also access deeper levels of sensitive data. This poses a complex security dilemma for IT leaders.

“Data security is one of the biggest concerns for AI adoption,” Kumar says. “Enterprises must ensure end-to-end encryption, access control policies and regulatory compliance when deploying AI assistants.”

FIND OUT: What are some key security considerations for embracing AI?

Other challenges include data governance and bias in AI decision-making. “There’s a real risk that AI assistants will inadvertently expose proprietary information,” McKeon-White says. “Without clear governance policies, AI assistants could pull data from unauthorized sources, leading to compliance violations.”

AI assistants can also make inaccurate and illogical recommendations if trained on biased data sets. That’s why experts recommend that organizations “invest in ethical AI frameworks and continuous model audits to mitigate bias risks,” Kingstone says.

The Future of AI Assistants

“AI assistants are no longer a futuristic concept — they are here, and they are transforming the way enterprises work,” Kingstone says. Businesses that integrate and train them properly will gain a significant competitive advantage.

AI agents will also grow in sophistication, becoming more intuitive and adaptable. Deploying them will also get easier with a shorter setup time.

“Right now, even the best AI assistants require weeks of training and customization,” McKeon-White says. “In the future, we’ll see AI models that dynamically adapt to business needs with minimal human intervention.”

DIG DEEPER: Drive better customer outcomes with AI agents and the help of CDW.

After that, “the next frontier is agentic AI, which are systems that not only assist users but also collaborate with other AI agents to execute complex tasks,” McKeon-White says.

But just like any employee in the workforce, an AI assistant needs to consistently deliver good work, prove ROI and be credible. That’s why widespread adoption will hinge on trust. Humans will also need more experience and positive outcomes with AI assistants to see them as reliable.

“Consumers and businesses alike will demand greater transparency in how AI assistants operate,” Kingstone says. “As AI systems become more autonomous, organizations must ensure they remain accountable and aligned with ethical guidelines. The challenge now is to ensure they are deployed responsibly, efficiently and in ways that drive real business value.”

UP NEXT: Who is better the human analyst or a machine learning model?