March 23, 2026
How To Use AI To Power Employee Productivity
Organizations that deploy secure end-user artificial intelligence tools help their workforce streamline tasks, boost productivity and increase operational efficiency.
As organizations seek new ways to improve employee productivity and engagement, artificial intelligence is becoming a practical tool for transforming how work gets done. Still, many enterprises struggle to move beyond experimentation to meaningful, secure adoption. End-user AI solutions such as Microsoft Copilot, Google Gemini, custom chatbots and contact center solutions can be embedded into everyday workflows to reduce friction and empower employees. When deployed strategically, these tools can effectively give employees their own AI-powered assistants, allowing them to offload rote workflows, automate routine tasks, and improve both the efficiency and the quality of their work. Organizations that measure these benefits, track them over time and make adjustments in response to the data will likely see the greatest ROI. Many turn to a trusted partner such as CDW to help define their AI strategies, enable initial deployment and manage and secure tools over time.
Schedule an AI Enablement Workshop with CDW to build a roadmap for deploying artificial intelligence tools such as Microsoft Copilot and chatbots.
As organizations seek new ways to improve employee productivity and engagement, artificial intelligence is becoming a practical tool for transforming how work gets done. Still, many enterprises struggle to move beyond experimentation to meaningful, secure adoption. End-user AI solutions such as Microsoft Copilot, Google Gemini, custom chatbots and contact center solutions can be embedded into everyday workflows to reduce friction and empower employees. When deployed strategically, these tools can effectively give employees their own AI-powered assistants, allowing them to offload rote workflows, automate routine tasks, and improve both the efficiency and the quality of their work. Organizations that measure these benefits, track them over time and make adjustments in response to the data will likely see the greatest ROI. Many turn to a trusted partner such as CDW to help define their AI strategies, enable initial deployment and manage and secure tools over time.
Schedule an AI Enablement Workshop with CDW to build a roadmap for deploying artificial intelligence tools such as Microsoft Copilot and chatbots.
Across industries, organizations are facing growing pressure to increase employee productivity while managing complex digital environments. Even in the era of AI, employees often continue to rely on manual processes, fragmented systems and disconnected knowledge bases that slow work and result in frustration.
Despite the presence of modern collaboration platforms, many employees and leaders continue to lack intelligent assistants that help them prioritize tasks, surface insights and automate routine activities. According to a 2025 Microsoft report, 80% of the global workforce (including employees and leaders) say they lack enough time or energy to do their work, and 53% of leaders say that productivity needs to increase. Additionally, more than half of leaders say their work is “chaotic and fragmented.”
As AI adoption accelerates, employees are increasingly experimenting with unsanctioned tools to fill productivity gaps, which can introduce new security, compliance and governance risks. This highlights a critical challenge: Organizations cannot sustainably improve employee productivity without providing secure, enterprise-ready AI capabilities directly within end-user tools.
Many leaders already recognize the importance of arming their workforce with powerful end-user AI solutions. According to the Microsoft report, 82% of leaders expect that their organization will use AI agents to meet the demand for more workforce capacity within the next 12 to 18 months. Also, CDW research published in 2025 shows that well over half of surveyed organizations have already deployed Microsoft Copilot (65%) and Google Gemini (61%).
The early evidence for improved productivity through AI is promising. According to a study published in Science, workers using a large language model were able to complete tasks 40% faster, with an 18% uptick in quality. Another study showed that customer support representatives were able to resolve 15% more issues per hour when they used a generative AI conversational assistant in their work. And a study conducted by the Federal Reserve Bank of St. Louis found that the average full-time employee was able to save 2.2 hours per week by using generative AI.
Still, implementation gaps remain, and many organizations struggle to achieve these improvements in their own business operations. A widely circulated 2025 MIT report claimed that 95% of existing generative AI pilots produce essentially no value, and one global survey of nearly 6,000 executives found that 80% have seen no discernable impact from AI so far.
Intentional, targeted investments in AI can help organizations reap the productivity benefits that many of their competitors are already achieving — especially when those investments connect closely to existing workflows. By embedding AI into the applications employees already use, organizations can reduce friction, eliminate repetitive work and allow teams to focus on higher-value activities.
98%
The percentage of organizations in which employees are using unsanctioned apps (“shadow IT”), including AI tools
Source: varonis.com, “Hidden Risks of Shadow AI,” June 30, 2025
Across industries, organizations are facing growing pressure to increase employee productivity while managing complex digital environments. Even in the era of AI, employees often continue to rely on manual processes, fragmented systems and disconnected knowledge bases that slow work and result in frustration.
Despite the presence of modern collaboration platforms, many employees and leaders continue to lack intelligent assistants that help them prioritize tasks, surface insights and automate routine activities. According to a 2025 Microsoft report, 80% of the global workforce (including employees and leaders) say they lack enough time or energy to do their work, and 53% of leaders say that productivity needs to increase. Additionally, more than half of leaders say their work is “chaotic and fragmented.”
As AI adoption accelerates, employees are increasingly experimenting with unsanctioned tools to fill productivity gaps, which can introduce new security, compliance and governance risks. This highlights a critical challenge: Organizations cannot sustainably improve employee productivity without providing secure, enterprise-ready AI capabilities directly within end-user tools.
Many leaders already recognize the importance of arming their workforce with powerful end-user AI solutions. According to the Microsoft report, 82% of leaders expect that their organization will use AI agents to meet the demand for more workforce capacity within the next 12 to 18 months. Also, CDW research published in 2025 shows that well over half of surveyed organizations have already deployed Microsoft Copilot (65%) and Google Gemini (61%).
The early evidence for improved productivity through AI is promising. According to a study published in Science, workers using a large language model were able to complete tasks 40% faster, with an 18% uptick in quality. Another study showed that customer support representatives were able to resolve 15% more issues per hour when they used a generative AI conversational assistant in their work. And a study conducted by the Federal Reserve Bank of St. Louis found that the average full-time employee was able to save 2.2 hours per week by using generative AI.
Still, implementation gaps remain, and many organizations struggle to achieve these improvements in their own business operations. A widely circulated 2025 MIT report claimed that 95% of existing generative AI pilots produce essentially no value, and one global survey of nearly 6,000 executives found that 80% have seen no discernable impact from AI so far.
Intentional, targeted investments in AI can help organizations reap the productivity benefits that many of their competitors are already achieving — especially when those investments connect closely to existing workflows. By embedding AI into the applications employees already use, organizations can reduce friction, eliminate repetitive work and allow teams to focus on higher-value activities.
Workforce Productivity: By the Numbers
38%
The percentage reduction in manual follow-up time that teams using AI meeting tools, such as automated notetakers, experience
Source: klu.so, “The State of AI and Productivity in 2025: Trends, Data, and Insights,” October 22, 2025
2 to 3
The average number of hours per week workers save by using AI tools
Source: varonis.com, “Hidden Risks of Shadow AI,” June 30, 2025
25%
The percentage of time employees save on email management and administrative tasks
Source: worklytics.co, “Generative AI's Real Impact on Workforce Productivity in 2025 — What Gartner & the Fed Data Really Say,” June 30, 2025
Workforce Productivity: By the Numbers
38%
The percentage reduction in manual follow-up time that teams using AI meeting tools, such as automated notetakers, experience
Source: klu.so, “The State of AI and Productivity in 2025: Trends, Data, and Insights,” October 22, 2025
2 to 3
The average number of hours per week workers save by using AI tools
Source: varonis.com, “Hidden Risks of Shadow AI,” June 30, 2025
25%
The percentage of time employees save on email management and administrative tasks
Source: worklytics.co, “Generative AI's Real Impact on Workforce Productivity in 2025 — What Gartner & the Fed Data Really Say,” June 30, 2025
- EMBEDDING AI IN EVERYDAY WORK
- MEASURING WORKFORCE IMPACT
- FROM STRATEGY TO SCALABLE ADOPTION
End-user AI delivers the greatest value when it is embedded directly into solutions that employees already use every day. Microsoft Copilot and Google Gemini are two of the clearest examples, as each is part of a suite of productivity and collaboration tools that are familiar to employees who have relied on them for years for word processing, spreadsheets, email, file storage and real-time co-authoring. By embedding AI in employees’ everyday workflows, organizations can accelerate adoption, maintain security controls and help workers attain a new set of skills that help them become more productive, efficient and innovative.
FASTER WORKFLOWS: Even at organizations with relatively low levels of AI maturity, employees are already using AI to automate routine tasks, summarize information and accelerate content creation. For instance, AI notetakers give meeting participants nearly instant access not only to comprehensive transcripts but also to distilled summaries and action items. Rather than manually reviewing conversations or reconstructing takeaways after meetings have already begun to fade from memory, employees can use embedded AI solutions to identify critical next steps. They can also use generative capabilities within word processing and email tools to help them brainstorm outlines, create first drafts and refine final language.
INTELLIGENT ASSISTANCE: The natural language interface of embedded enterprise AI systems essentially gives workers access to an on-demand “assistant” to help track down information and complete tasks that previously required specialized knowledge. For example, rank-and-file employees across business units can now analyze data without needing to write SQL queries, be Excel experts or understand complex coding syntax. Instead, they can interact with AI tools in plain language to retrieve insights, summarize information or complete tasks. This removes technical barriers and helps employees extract value from enterprise data that might otherwise sit idle.
ROLE-BASED VALUE: Productivity gains from AI look different across roles. Not every AI tool or feature will benefit every worker, and organizations must align their tools and training to specific employee roles and workflows. The contact center is a prime example of a highly specialized department that organizations can optimize with the right set of AI solutions. By surfacing information more quickly and enabling faster customer responses, AI tools can reduce the average handling time for each call. They can also automatically detect customer sentiment, summarize calls for later reference and even conduct preliminary call scoring to help inform employee training.
SECURITY BY DESIGN: The rise of generative AI has opened up a whole new set of potential vulnerabilities, including prompt injection and data poisoning. But one of the most dangerous threats will be familiar to nearly all business and IT leaders: shadow IT. When organizations don’t make enterprise AI tools available to employees, they will usually find their own consumer-grade solutions, the same way workers sometimes use personal file-sharing accounts to store and send sensitive corporate documents. But by embedding AI into everyday tools, organizations can reduce the danger of shadow AI.
UPSKILLING EMPLOYEES: Many observers continue to express concern that employees will be replaced by AI tools. But so far, at least, the organizations having the greatest success are largely using AI for augmentation, not replacement. With the right training and tools, AI opens up a whole new set of abilities for workers: Nondevelopers can suddenly build prototypes of digital solutions, nonanalysts can perform data exploration to uncover hidden areas of value for the business, and non-designers can instantly generate a set of images or layouts that fit their vision to facilitate communication with creative teams. In short, embedded AI tools are helping employees operate at a higher level, with little to no additional training.
Click Below To Continue Reading
Effective End-User AI Solutions
For some highly specialized tasks, organizations may need custom-built AI tools. However, a number of popular off-the-shelf solutions have made their way into enterprises in virtually every industry. While some of these tools are aimed at specific business units, others are all-purpose AI chatbots designed to help users across the organization be more productive and efficient in their work.
MICROSOFT COPILOT: This AI assistant embedded in Microsoft 365 applications helps employees draft documents, summarize meetings, analyze spreadsheets and automate repetitive knowledge work tasks.
GOOGLE GEMINI: AI features across Google Workspace help employees generate content, organize information, analyze data and collaborate more efficiently within familiar tools such as email.
CUSTOM ENTERPRISE CHATBOTS: Some organizations deploy bespoke internal AI assistants trained on company knowledge to help employees find information, complete tasks and navigate enterprise systems.
CONTACT CENTER AI: Customer service is an area where many companies have enthusiastically embraced automation. AI tools in the contact center provide real-time guidance for agents, call summarization and quality metrics.
AI-ENABLED DEVICES: A new generation of laptops and mobile devices integrates on-device AI capabilities that enhance device performance, security and even battery life.
It’s relatively easy to track adoption of AI tools across the enterprise. But to measure the true impact of their AI efforts, organizations must evaluate how AI affects specific workflows, employee roles and business outcomes. Research shows that AI-driven workforce solutions can deliver measurable productivity, engagement and innovation benefits. By carefully tracking progress toward these outcomes, leaders can build internal support for AI initiatives and gather valuable data to help guide future investments.
PRODUCTIVITY GAINS: According to a 2025 CDW survey, 48% of IT leaders and decision-makers say they feel “very strongly” that AI can help them achieve faster innovation (39% feel “somewhat strongly”). In highly structured environments such as contact centers, leaders can measure improvements through established key performance indicators (KPIs), such as average call handling time. For knowledge workers, gains may appear in the form of shorter task cycles or improved quality of outputs. A January 2026 Deloitte report notes that under 60% of employees with access to AI tools currently use those tools in their daily workflows, similar to the year before. Deloitte writes: “This suggests that while access is widening, enterprise AI remains underutilized, and its productivity and innovation potential are still largely untapped.”
EMPLOYEE EXPERIENCE: To track more qualitative benefits, such as reduced friction, greater job satisfaction and enhanced creativity, organizations may need to conduct employee surveys. While productivity metrics capture task efficiency, employee sentiment reveals whether AI tools are genuinely improving the day-to-day work experience, which can have a significant impact on recruitment and retention. In employee surveys, leaders might ask workers whether AI tools help them feel better supported, less burdened by repetitive tasks or more empowered to focus on meaningful contributions. According to Yomly, a human resources and payroll software provider, AI tools boost employee satisfaction by 33%, reduce burnout by 30% and help 70% of employees achieve better work-life balance.
CONTINUOUS IMPROVEMENT: Because AI adoption is not a one-time event, leaders should establish ongoing measurement cycles, regularly reviewing productivity metrics to ensure that AI continues delivering meaningful improvements. In fact, some of the benefits of AI may not show up at all at first, especially for organizations that are still in the process of learning which tools will best support specific workflows and job roles. According to Deloitte, 84% of companies have not yet redesigned jobs or the nature of work itself around AI capabilities. If possible, organizations should benchmark performance before AI tools are deployed and compare these numbers against post-deployment outcomes. By grounding AI deployment in clearly defined metrics, leaders can move beyond anecdotal success stories and demonstrate measurable operational impact.
COMPETITIVE ADVANTAGE: Improved productivity, efficiency, employee engagement and customer satisfaction are all desirable benefits. But ultimately, they are all means to the same end: a competitive edge in the marketplace. Organizations that successfully deploy AI-powered workforce solutions better position themselves to respond to shifting market conditions, outpace slower-moving rivals and attract top talent. A durable competitive edge is nearly impossible to measure in real time, but leaders can track leading indicators such as time to market for new products and services, customer retention rates, and revenue growth relative to industry benchmarks. In one 2025 European market survey, 45% of business leaders said their organizations had already gained a competitive advantage through AI.
Successfully enabling an AI-driven workforce requires more than licensing tools. Organizations must align AI initiatives with business objectives, prioritize use cases and prepare employees for adoption. Enablement workshops, pilots and deployment accelerators from a trusted partner such as CDW can help organizations move from pilot to production while maximizing value and reducing risk.
DEFINE VISION AND VALUE: Before selecting tools or launching pilots, leaders must define what AI success will look like within their organization. Rather than letting technology advancements or the actions of competitors guide their efforts, leaders should tie their investments to measurable business outcomes such as improved productivity, faster time to market or improved customer satisfaction. Establishing clear objectives upfront prevents sprawl, aligns stakeholders and creates a framework for measuring progress over time.
ACCELERATE ENABLEMENT: CDW’s AI Enablement Workshops help organizations maximize the value of their AI investments by equipping employees and leaders with the knowledge and skills to successfully implement their AI roadmaps. These sessions are designed to help stakeholders understand the potential of AI, how they can apply the technology to their specific business cases, and how to seamlessly integrate new tools into their existing workflows and IT environments.
DEPLOY EMBEDDED AI TOOLS: Proven end-user tools such as Microsoft Copilot and Google Gemini embed AI directly into the tools that employees already use, helping to accelerate adoption and value. CDW supports Microsoft Copilot and Google Gemini licensing, QuickStart services, and deployment accelerators to quickly stand up end-user AI at scale. CDW can also help organizations establish identity and security processes to ensure AI capabilities do not create new vulnerabilities.
DEVELOP CUSTOM AI TOOLS: While off-the-shelf AI tools address common productivity needs, many organizations require tailored solutions aligned to specific workflows. These may include custom enterprise chatbots and AI support agents that streamline knowledge access and automate repetitive tasks. Through proof-of-concept pilots and phased rollouts, organizations can test solutions on service desks, in human resources portals or in internal support environments before scaling across the enterprise.
ESTABLISH AI GOVERNANCE: Without strong governance and cybersecurity practices, AI tools can expose organizations to a new set of risks and threats. For example, organizations that take governance shortcuts may inadvertently expose confidential HR information to unauthorized internal users or allow their intellectual property to be used to train public AI models.
ADOPT AI-ENABLED DEVICES: Increasingly, vendors are embedding AI capabilities not only in software tools but in end-user devices such as laptops. Device-level AI can reduce latency for productivity tasks, improve battery life, and boost security by automatically detecting anomalous behavior and identifying suspicious activity.
OPTIMIZE THE CONTACT CENTER: The contact center offers one of the clearest opportunities for measurable near-term AI impact. Through AI-powered knowledge retrieval, real-time assistance, sentiment detection and call summaries, organizations can reduce average handling time, improve training and enhance the customer experience. By tracking structured KPIs, leaders can quantify these improvements, building the case for the value of AI across the organization.
MANAGE THE LIFECYCLE: Successful AI adoption requires continuous evaluation and adjustment. Leaders should regularly assess usage patterns, workflow impact and employee feedback to ensure tools remain aligned with evolving business needs. Organizations will also need to scale up high-value AI tools while decommissioning solutions that add cost and complexity instead of value. By treating AI as an evolving capability rather than a static deployment, organizations can sustain productivity gains and adapt to a technology landscape that is constantly changing.
- EMBEDDING AI IN EVERYDAY WORK
- MEASURING WORKFORCE IMPACT
- FROM STRATEGY TO SCALABLE ADOPTION
End-user AI delivers the greatest value when it is embedded directly into solutions that employees already use every day. Microsoft Copilot and Google Gemini are two of the clearest examples, as each is part of a suite of productivity and collaboration tools that are familiar to employees who have relied on them for years for word processing, spreadsheets, email, file storage and real-time co-authoring. By embedding AI in employees’ everyday workflows, organizations can accelerate adoption, maintain security controls and help workers attain a new set of skills that help them become more productive, efficient and innovative.
FASTER WORKFLOWS: Even at organizations with relatively low levels of AI maturity, employees are already using AI to automate routine tasks, summarize information and accelerate content creation. For instance, AI notetakers give meeting participants nearly instant access not only to comprehensive transcripts but also to distilled summaries and action items. Rather than manually reviewing conversations or reconstructing takeaways after meetings have already begun to fade from memory, employees can use embedded AI solutions to identify critical next steps. They can also use generative capabilities within word processing and email tools to help them brainstorm outlines, create first drafts and refine final language.
INTELLIGENT ASSISTANCE: The natural language interface of embedded enterprise AI systems essentially gives workers access to an on-demand “assistant” to help track down information and complete tasks that previously required specialized knowledge. For example, rank-and-file employees across business units can now analyze data without needing to write SQL queries, be Excel experts or understand complex coding syntax. Instead, they can interact with AI tools in plain language to retrieve insights, summarize information or complete tasks. This removes technical barriers and helps employees extract value from enterprise data that might otherwise sit idle.
ROLE-BASED VALUE: Productivity gains from AI look different across roles. Not every AI tool or feature will benefit every worker, and organizations must align their tools and training to specific employee roles and workflows. The contact center is a prime example of a highly specialized department that organizations can optimize with the right set of AI solutions. By surfacing information more quickly and enabling faster customer responses, AI tools can reduce the average handling time for each call. They can also automatically detect customer sentiment, summarize calls for later reference and even conduct preliminary call scoring to help inform employee training.
SECURITY BY DESIGN: The rise of generative AI has opened up a whole new set of potential vulnerabilities, including prompt injection and data poisoning. But one of the most dangerous threats will be familiar to nearly all business and IT leaders: shadow IT. When organizations don’t make enterprise AI tools available to employees, they will usually find their own consumer-grade solutions, the same way workers sometimes use personal file-sharing accounts to store and send sensitive corporate documents. But by embedding AI into everyday tools, organizations can reduce the danger of shadow AI.
UPSKILLING EMPLOYEES: Many observers continue to express concern that employees will be replaced by AI tools. But so far, at least, the organizations having the greatest success are largely using AI for augmentation, not replacement. With the right training and tools, AI opens up a whole new set of abilities for workers: Nondevelopers can suddenly build prototypes of digital solutions, nonanalysts can perform data exploration to uncover hidden areas of value for the business, and non-designers can instantly generate a set of images or layouts that fit their vision to facilitate communication with creative teams. In short, embedded AI tools are helping employees operate at a higher level, with little to no additional training.
Click Below To Continue Reading
Effective End-User AI Solutions
For some highly specialized tasks, organizations may need custom-built AI tools. However, a number of popular off-the-shelf solutions have made their way into enterprises in virtually every industry. While some of these tools are aimed at specific business units, others are all-purpose AI chatbots designed to help users across the organization be more productive and efficient in their work.
MICROSOFT COPILOT: This AI assistant embedded in Microsoft 365 applications helps employees draft documents, summarize meetings, analyze spreadsheets and automate repetitive knowledge work tasks.
GOOGLE GEMINI: AI features across Google Workspace help employees generate content, organize information, analyze data and collaborate more efficiently within familiar tools such as email.
CUSTOM ENTERPRISE CHATBOTS: Some organizations deploy bespoke internal AI assistants trained on company knowledge to help employees find information, complete tasks and navigate enterprise systems.
CONTACT CENTER AI: Customer service is an area where many companies have enthusiastically embraced automation. AI tools in the contact center provide real-time guidance for agents, call summarization and quality metrics.
AI-ENABLED DEVICES: A new generation of laptops and mobile devices integrates on-device AI capabilities that enhance device performance, security and even battery life.
It’s relatively easy to track adoption of AI tools across the enterprise. But to measure the true impact of their AI efforts, organizations must evaluate how AI affects specific workflows, employee roles and business outcomes. Research shows that AI-driven workforce solutions can deliver measurable productivity, engagement and innovation benefits. By carefully tracking progress toward these outcomes, leaders can build internal support for AI initiatives and gather valuable data to help guide future investments.
PRODUCTIVITY GAINS: According to a 2025 CDW survey, 48% of IT leaders and decision-makers say they feel “very strongly” that AI can help them achieve faster innovation (39% feel “somewhat strongly”). In highly structured environments such as contact centers, leaders can measure improvements through established key performance indicators (KPIs), such as average call handling time. For knowledge workers, gains may appear in the form of shorter task cycles or improved quality of outputs. A January 2026 Deloitte report notes that under 60% of employees with access to AI tools currently use those tools in their daily workflows, similar to the year before. Deloitte writes: “This suggests that while access is widening, enterprise AI remains underutilized, and its productivity and innovation potential are still largely untapped.”
EMPLOYEE EXPERIENCE: To track more qualitative benefits, such as reduced friction, greater job satisfaction and enhanced creativity, organizations may need to conduct employee surveys. While productivity metrics capture task efficiency, employee sentiment reveals whether AI tools are genuinely improving the day-to-day work experience, which can have a significant impact on recruitment and retention. In employee surveys, leaders might ask workers whether AI tools help them feel better supported, less burdened by repetitive tasks or more empowered to focus on meaningful contributions. According to Yomly, a human resources and payroll software provider, AI tools boost employee satisfaction by 33%, reduce burnout by 30% and help 70% of employees achieve better work-life balance.
CONTINUOUS IMPROVEMENT: Because AI adoption is not a one-time event, leaders should establish ongoing measurement cycles, regularly reviewing productivity metrics to ensure that AI continues delivering meaningful improvements. In fact, some of the benefits of AI may not show up at all at first, especially for organizations that are still in the process of learning which tools will best support specific workflows and job roles. According to Deloitte, 84% of companies have not yet redesigned jobs or the nature of work itself around AI capabilities. If possible, organizations should benchmark performance before AI tools are deployed and compare these numbers against post-deployment outcomes. By grounding AI deployment in clearly defined metrics, leaders can move beyond anecdotal success stories and demonstrate measurable operational impact.
COMPETITIVE ADVANTAGE: Improved productivity, efficiency, employee engagement and customer satisfaction are all desirable benefits. But ultimately, they are all means to the same end: a competitive edge in the marketplace. Organizations that successfully deploy AI-powered workforce solutions better position themselves to respond to shifting market conditions, outpace slower-moving rivals and attract top talent. A durable competitive edge is nearly impossible to measure in real time, but leaders can track leading indicators such as time to market for new products and services, customer retention rates, and revenue growth relative to industry benchmarks. In one 2025 European market survey, 45% of business leaders said their organizations had already gained a competitive advantage through AI.
Successfully enabling an AI-driven workforce requires more than licensing tools. Organizations must align AI initiatives with business objectives, prioritize use cases and prepare employees for adoption. Enablement workshops, pilots and deployment accelerators from a trusted partner such as CDW can help organizations move from pilot to production while maximizing value and reducing risk.
DEFINE VISION AND VALUE: Before selecting tools or launching pilots, leaders must define what AI success will look like within their organization. Rather than letting technology advancements or the actions of competitors guide their efforts, leaders should tie their investments to measurable business outcomes such as improved productivity, faster time to market or improved customer satisfaction. Establishing clear objectives upfront prevents sprawl, aligns stakeholders and creates a framework for measuring progress over time.
ACCELERATE ENABLEMENT: CDW’s AI Enablement Workshops help organizations maximize the value of their AI investments by equipping employees and leaders with the knowledge and skills to successfully implement their AI roadmaps. These sessions are designed to help stakeholders understand the potential of AI, how they can apply the technology to their specific business cases, and how to seamlessly integrate new tools into their existing workflows and IT environments.
DEPLOY EMBEDDED AI TOOLS: Proven end-user tools such as Microsoft Copilot and Google Gemini embed AI directly into the tools that employees already use, helping to accelerate adoption and value. CDW supports Microsoft Copilot and Google Gemini licensing, QuickStart services, and deployment accelerators to quickly stand up end-user AI at scale. CDW can also help organizations establish identity and security processes to ensure AI capabilities do not create new vulnerabilities.
DEVELOP CUSTOM AI TOOLS: While off-the-shelf AI tools address common productivity needs, many organizations require tailored solutions aligned to specific workflows. These may include custom enterprise chatbots and AI support agents that streamline knowledge access and automate repetitive tasks. Through proof-of-concept pilots and phased rollouts, organizations can test solutions on service desks, in human resources portals or in internal support environments before scaling across the enterprise.
ESTABLISH AI GOVERNANCE: Without strong governance and cybersecurity practices, AI tools can expose organizations to a new set of risks and threats. For example, organizations that take governance shortcuts may inadvertently expose confidential HR information to unauthorized internal users or allow their intellectual property to be used to train public AI models.
ADOPT AI-ENABLED DEVICES: Increasingly, vendors are embedding AI capabilities not only in software tools but in end-user devices such as laptops. Device-level AI can reduce latency for productivity tasks, improve battery life, and boost security by automatically detecting anomalous behavior and identifying suspicious activity.
OPTIMIZE THE CONTACT CENTER: The contact center offers one of the clearest opportunities for measurable near-term AI impact. Through AI-powered knowledge retrieval, real-time assistance, sentiment detection and call summaries, organizations can reduce average handling time, improve training and enhance the customer experience. By tracking structured KPIs, leaders can quantify these improvements, building the case for the value of AI across the organization.
MANAGE THE LIFECYCLE: Successful AI adoption requires continuous evaluation and adjustment. Leaders should regularly assess usage patterns, workflow impact and employee feedback to ensure tools remain aligned with evolving business needs. Organizations will also need to scale up high-value AI tools while decommissioning solutions that add cost and complexity instead of value. By treating AI as an evolving capability rather than a static deployment, organizations can sustain productivity gains and adapt to a technology landscape that is constantly changing.
Ken Drazin
Director of Digital Experience, CDW
