Gen AI drives outcomes, right? Or is it just a productivity driver?

I’ve warned CIOs against championing productivity drivers as the main benefit of gen AI capabilities, including LLMs and AI agents. Say productivity and the CFO thinks headcount reduction.

I believe the short-term benefits of gen AI are not about productivity. Seek to increase employee capabilities and discover how gen AI drives outcomes.   

Gen AI drives outcomes by increasing employee capabilities

Employees can use gen AI to do things and drive outcomes they couldn’t easily do before. These capabilities may improve productivity by automating tasks or scaling operational steps. But I am really seeking how employees drive outcomes with gen AI that previously would have been too complicated, required too many people with different skill sets, or needed access to specialized technologies.

I’m not just speaking about human-in-the-middle or human-at-the-helm approaches where people complete steps or have oversight in a gen AI automation or agent. I’m looking forward to the reverse, where people are responsible, and gen AI is an enabler.

Experts shared how gen AI drives outcomes by helping people increase their skills and capabilities.

1. Connect customer intelligence across digital and real-world experiences

Ask marketers what’s hard to do at scale and accurately, and they’ll say attribution. It requires identifying and assigning credit to the various touchpoints and channels contributing to a customer’s decision to purchase, sign up for an event, or take another desired action. Capturing all the nuances in a digital customer’s journey has challenges. For many businesses with physical locations like retail, universities, or hospitals, connecting the physical and digital worlds of highly unstructured data can be a competitive differentiator.

“With gen AI, marketers and operations leaders can draw nuanced insights about the customer experience at physical locations from unstructured data, such as social media chatter, online reviews, photos, and open-ended survey questions, and apply those insights to business decisions at scale,” says John Mazur, CEO of Chatmeter. “They can use natural language prompts to understand how customers feel about new products or quality of service and receive real-time insights from thousands of locations at once–something that wasn’t possible before.”

How is gen AI a game changer? Multi-location marketing requires a mix of marketing strategies and connecting the dots on what’s working. Marketers can improve SEO, optimize social media with local accounts, personalize paid advertising campaigns, and develop local partnerships. Gen AI can help customers answer questions on customer segments or buying personas, enabling a more targeted approach for driving the desired outcomes.   

“At this level of customer intelligence, multi-location businesses like retailers and restaurants can make large-scale operational shifts that significantly impact their customers,” Mazur says.

2. Improve customer satisfaction in call centers

I recently vented about several poor customer experiences and how agentic AI can drive customer success. Count me as one of the 69% of consumers who switched brands after just one bad experience.

So, what can gen AI do to improve call center quality?

Rob Scudiere, CTO at Verint, says one example is a specialized bot that creates call summaries in a customer contact center. “This monotonous and required micro-workflow can be automated with gen AI so that contact center agents can spend more time with customers. As a result, agents have more capacity, customer experience (CX) is enhanced, and either cost savings or revenue generation – or both – are increased.”

Scudiere shares this bonus for companies embracing specialized micro-workflow bots. “It serves as a minimally disruptive entry point for AI adoption, offering immediate ROI and building confidence in the potential of gen AI to drive rapid business outcomes,” Scudiere says.

3. Simplify understanding of complex compliance requirements

One AI legislation tracker lists over 150 U.S. bills in progress, and another tracks AI laws and policies in 25 countries.

A company’s legal, risk management, and AI governance leaders may have to track these regulations in detail. But that’s not sufficient when regulations and technology capabilities are changing rapidly. Department leaders, including CHROs, CIOs, and CMOs, must also understand whether and which regulations impact their operations.

“AI agents are particularly valuable to business owners and HR professionals tasked with sifting through complex compliance requirements,” says Mike Tria, CTO of Gusto. “AI assistants can help navigate local mandates and regulations to make compliance easier and in language you don’t need a law degree to understand.”

4. Enable knowledgebases with intelligent gen AI search capabilities

How many platforms and SaaS have embedded search engines with a limited scope of what data they index? How can organizations connect knowledge across geographies, languages, and departments to help employees find relevant information and internal experts when working on an initiative?

“Gen AI integrated with AI search streamlines tasks that once required multiple disjointed tools and hours of manual effort,” says Steve Mayzak, global managing director of search AI at Elastic. “Rather than jumping between apps to find answers, AI search retrieves relevant information through natural language queries and summarizes key insights for daily tasks.”

Don’t just think about searching documents and unstructured information stored in SaaS tools. If you work backward from how departments and leaders make decisions, you’ll find they use different analytics tools, reports, and data sources. Not every department has a data science team to integrate and model the data, which is where gen AI can provide value as an information analyst.

“Gen AI also helps employees analyze vast amounts of disparate data and reason across multiple domains to recommend optimal solutions and accelerate decision-making,” adds Mayzak. “Whether it’s a marketer searching for customer data or an HR professional looking up benefits details, employees can quickly access the information they need without digging through multiple sources.”

5. Accelerate adoption of citizen development and data science

Speaking of citizen data science. Self-service data visualization and other citizen data science tools paved the way for dashboarding, data visualization, reporting, and analytics to move from a data science or IT responsibility to a business analyst’s capability. Gen AI can further these efforts by replacing writing SQL, developing pivot tables, and writing Python analytics functions with natural language prompts and code generations.  

“AI can also break down technical barriers by democratizing access to analytics and software development tools,” says Tria of Gusto. “AI lowers the technical bar needed for any employee to build. Technical and non-technical employees can build AI-powered recipes that other employees can replicate, edit, and use 10x-ing their abilities to solve customer problems. “

6. Find the root causes of security threats faster

Network operations centers (NOCs) have been using AIOps to improve incident recovery time (MTTR) and aid in problem root cause analysis. AIOps platforms generally use ML and statistical techniques to connect and correlate alerts and observability data.

However, the NOC challenge is generally simpler than what security operation centers (SOCs) must perform.

SOCs must contend with long-running security issues – ones that infiltrated and stayed dormant for long durations. To detect threats, they must also connect more data sources, including third-party threat databases. When there’s a security issue, they have limited time to decipher material incidents from manageable vulnerabilities and issues.

“In an age of growing cybersecurity threats, gen AI has the power to detect threats at unprecedented rates and flag them to local IT teams in real-time,” says Anant Adya, EVP at Infosys Cobalt. “It can also provide those teams with large sets of information on where the threat came from and what the next steps should be. From there, teams can work to address the issue before it becomes a larger problem or puts an organization at further risk.”

7. Improve decision-making in complex areas

AI agents have the potential to transform employee experiences. Look beyond productivity improvements – I can do X tasks faster. Seek the ones that become gen AI force multipliers. Consider how employees can do (Y * X) faster, at higher quality, and with improved business outcomes.   

“Unlike traditional AI models that passively process data and follow pre-programmed instructions, agentic AI can take initiative, make autonomous decisions, and dynamically adapt to its environment,” says Ashutosh Garg, co-CEO and co-founder of Eightfold AI. “It acts as an independent entity capable of setting goals, strategizing, and executing plans with minimal human intervention. Organizations can build intelligent, proactive systems that enhance efficiency, accuracy, and decision-making by integrating agentic AI, working alongside people to drive innovation.”

Need examples? Look for opportunities where too much information moves too fast for people to keep up with on their own. A supply chain leader tracking the impacts of tariff announcements. An HR leader reviewing hundreds of job applicants after a recent layoff at a competitor. A compliance officer sifting through hundreds of contracts to find risks during M&A due diligence.

Find how gen AI improves employee capabilities. Productivity improvements are the byproduct.