Optimizing GenAI for People and Processes

Generative AI (GenAI) innovations are revolutionizing the way we work at a breakneck speed. Tasks that once required specialized teams or external suppliers are now within reach of enterprise employees, who are writing, coding, analyzing, and making predictions more efficiently and with fewer in-house skills than ever before.

However, leveraging GenAI across an entire business—what many see as the ultimate goal of this technological era—is proving to be a more complex challenge. Organizations aim to boost productivity across various teams and functions, but the journey is often longer and costlier than anticipated. The hidden truth about generative AI is that executives struggle to integrate its components and achieve consistently accurate outputs. They also face tough decisions between cost and scalability.

Individual-focused solutions, like copilot-type applications, excel at specific personal tasks such as drafting sales emails, kickstarting blogs, and conducting research. Yet, these tools are often limited in scope, producing outputs that aren't integrated into the broader business framework. They lack the consistency and scalability required for business settings. On the other hand, enterprise-level AI solutions that automate processes such as expense report audits or supply chain management can greatly reduce tedious work and errors but are often too specialized to have broad applicability.

Some companies, however, have cracked the code on optimizing GenAI for both people and processes. Here are a few shining examples:

Companies Successfully Optimizing GenAI

1. Global Cosmetics Company

A leading cosmetics brand uses GenAI to automate content creation from its product database to the "digital shelf" across hundreds of products and numerous e-retail distribution channels. Product descriptions frequently change due to new positioning, competitive adjustments, and seasonal events. With GenAI, the company can deliver updated content to dozens of countries in local languages, adhering to legal, regulatory, and cultural norms. This not only gets new product materials to market weeks earlier and boosts online conversions but also empowers brand owners and regional managers by providing nearly market-ready content, reducing unproductive back-and-forth.

2. CRM Platform Leader

This company has built various GenAI applications to handle complex cross-company workflows. From executing multiple product launches annually to hosting hundreds of global events, each task involves a detailed "bill of materials" that touches multiple departments, including product, UX, sales, marketing, customer support, and executive teams. By tapping into knowledge sources and style guides, and automating the creation of materials—from support articles to executive commentary—the company significantly reduces time and organizational thrash, elevating stakeholders' roles from tactical to strategic.

3. Data Protection Innovator

Recently, this company launched a new product and used GenAI to develop an internal sales enablement app. The app taps into the company’s knowledge base, messaging, and brand sources to answer questions about customer personas, use cases, success stories, product details, benefits, and key messages. Hundreds of sales professionals worldwide now receive accurate, real-time answers, enabling them to have intelligent, helpful conversations with prospects, customers, and partners, thus eliminating the usual friction of getting questions answered.

Key Takeaways from Successful GenAI Projects

These successful GenAI projects share three crucial elements that allowed each company to deliver value quickly with minimal expense and effort:

1. Shared Resources and Customization: They utilized a set of trained large language models (LLMs), retrieval capabilities, and company-specific guardrails across the business, customizing the final application to specific functions or workflows. This approach ensures quick rollout, accurate output, and consistent branding across AI deliverables.

2. Collaborative Deployment: By involving stakeholders early, iterating quickly with prototypes, and promoting knowledge sharing and skill-building across teams, these companies made their teams self-sufficient and capable of swiftly advancing new use cases and solutions.

3. Relentless Improvement: They focused on identifying and resolving "uglies" in the system—such as bugs, hallucinations, and data indexing issues. This proactive approach ensured higher accuracy and quality of AI outputs for all stakeholders.

Optimizing GenAI for both people and processes isn't just possible—it's happening now. By following the lead of these innovative companies, organizations can harness the full potential of generative AI, transforming workflows, empowering employees, and driving business success.

As we look to the future, the possibilities for optimizing GenAI to enhance both people and processes are boundless. The key lies in leveraging shared resources, fostering collaboration, and continuously improving system accuracy. Companies that embrace these strategies will not only streamline operations but also empower their teams to achieve greater heights.

By integrating GenAI thoughtfully and strategically, businesses can transform workflows, enhance productivity, and unlock new opportunities for innovation and growth. How is your organization utilizing GenAI to enhance productivity and streamline processes? Share your thoughts and insights in the comments below as I learn just as much from you as you do from me.