Bust through the Hype and Build Practical AI Solutions that Drive Rapid, Measurable Productivity for Business

Early AI adopters that are focused on realizing opportunities for enhancing customer and employee experience, operational efficiency and, ultimately, the bottom line, are now moving the focus of their investment focus to bring these tools out of development and into full-scale production.

Recent research shows 72% of organizations have adopted generative AI this year; yet only a small portion have been successful in implementing the technology at scale. Even fewer have been able to see and measure a real productivity gain for their businesses. Clearly, organizations are enthused by generative AI, but when it comes to moving beyond ideation to implementation, the momentum is often lost.

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Launching a product into production, scaling it and integrating generative AI in daily workflows requires an actionable framework driven by talented teams – championed and held accountable by top leadership.

Fostering a culture of innovation starts at the top

According to Gartner, CEOs expect that generative AI will “spur a productivity boon.” While this opportunity is driving increasing interest in the technology, it also raises the question: How do we channel this excitement into a clear path toward results?

CEOs and leadership boards play a crucial role in driving innovation while balancing business priorities and growth opportunities. However, the current AI hype demands a strategic AI agenda that is actively championed by top executives. Innovation-focused leadership must recognize that long-term AI success is driven not only by technological expertise but also by cultivating a shift in the organization’s mindset and culture.

A top-down approach is essential in this transformation. Leaders should start by empowering employees at all levels to propose tools and solutions that can directly enhance their productivity, efficiency, or ability to generate revenue. By actively encouraging input from key stakeholders—such as those in sales and marketing, supply chain, HR, finance, and engineering—leadership ensures that these employees feel motivated and supported in offering new ideas to overcome everyday challenges.

This approach keeps the workforce engaged and passionate about their work. It reinforces leadership’s commitment to addressing the obstacles that hinder productivity and allowing employees to focus on what truly matters.

How to derive action from excitement

While not every AI solution is ready for immediate enterprise-wide use, especially in complex IT environments with numerous data sources, most businesses can find targeted, low-risk high-reward applications where AI adds immediate value.

Take the idea of calling directly on employees to develop ideas that will improve their daily workday.  World Wide Technology recently applied this method to its global organization, calling on over 10,000 employees to help identify AI solutions that could run effectively on the company’s existing IT infrastructure and have the greatest impact on productivity or revenue generation.

WWT leaders advocated for engagement through internal workshops that spurred ideation and discussion on the ROI of each proposal. The team then selected a few tools to begin development, including an AI-powered RFP Assistant for direct sales impact, a chatbot named Atom Ai with ChatGPT like abilities adding to general employee productivity, and a Coding Assistant with the ability to run securely on-prem and help developer productivity.

The tools demonstrated significant enhancement to daily workflow. For an RFP team that receives over 800 requests per year, the RFP Assistant already has shown initial results, saving more than 50% of the time it takes to complete a response. Atom Ai is now live for all WWT employees and has saved between 6-12 hours a week in A/B testing. It is currently helping our salesforce comb through our IP in record speed – and we’re starting to see an uptick in lead-funnel conversion speeds amongst top Atom users.

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Implementing generative AI requires effective measurement frameworks

While it is satisfying to see these AI-powered tools come to life in development, the process cannot stop there. Understanding how the tools perform, how it impacts the daily work of the user, and where it falls short of generating the productivity needed to validate the ROI is integral to bringing the tools into production and accelerating adoption.

Additionally, proper controls must be in place. Setting standards and following frameworks like those established by UNESCO while still in the development phase is critical to laying a globally consistent approach for ethical and safe AI practices during full-scale production.

Measuring the results can take many forms, but it is important for teams to prioritize this step to be successful in implementation. For example, releasing the tool to a small group of users and asking a defined set of questions will generate feedback that can inform further development. The team can also assess response time of the tool, types of queries or frequency of use to understand where the high value use cases lie. This approach sets the foundation that makes it manageable to make incremental improvements and ensure the product is ready for implementation.

Measurement is not only important for demonstrating business impact, but it is also a meaningful way to drive adoption. Showcasing how AI-powered solutions can directly enhance existing workflows and day-to-day challenges will encourage usership and help ensure the implementation of the tool is successful.

This process should be led by the c-suite. AI has the potential be disruptive, from customer experiences to marketing to back-end operations to executive decision-making. However, it will require a paradigmatic organizational shift rather than a one-off technology investment. Successful organizations will be those that understand how to use the AI hype to motivate a team to experiment with ideas that help improve the employee experience and impact the bottom line.

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