AI: The Unlikely Hero in a Challenging Economic Climate

SCOTTSDALE, Ariz. – January 16, 2026 – While economic pressures like inflation and rising interest rates cast a long shadow over revenue forecasts, a new report indicates that a vast majority of business leaders are turning to artificial intelligence as their primary engine for growth and efficiency. A landmark study by the Alexander Group, a premier go-to-market consultancy, reveals a stark contrast in executive sentiment: 78% of commercial leaders surveyed identified AI adoption as a leading driver of revenue growth. Conversely, 61% pointed to inflation and interest rates as drivers of revenue decline.

This data suggests a pivotal shift in corporate strategy, where technology is no longer just a tool for optimization but a critical tailwind pushing against macroeconomic headwinds. “Commercial leaders are grappling with their fair share of challenges,” said Sean Higgins, principal at Alexander Group, in the announcement. “The only significant expected tailwind is coming from automation and AI adoption. Our research shows that leading firms are making strategic, targeted investments to reduce costs and boost efficiency—both internally and among their customer base.” The findings, based on conversations with over 100 executives across diverse sectors, paint a clear picture of AI as a strategic imperative for survival and growth.

A New Commercial Playbook Powered by AI

The abstract concept of AI driving growth is now translating into concrete applications across sales, marketing, and service departments. The Alexander Group research pinpoints the most impactful AI-powered solutions currently being deployed by commercial teams. Nearly half of leaders (47%) are using generative AI chat and agents to facilitate complex product or service configurations, a task that traditionally required significant time and specialized human expertise.

Following closely are outbound agentic lead generation (44%) and agentic customer service management (42%). These 'agentic' systems represent a leap forward, capable of acting autonomously to identify, qualify, and even initiate contact with potential leads or resolve customer issues with minimal human oversight. This automation is powered by sophisticated platforms from tech giants like Salesforce, Microsoft, and Google, which provide the underlying infrastructure for companies to build AI-powered chatbots, virtual assistants, and analytical models. These tools are being integrated into existing CRM and customer service platforms from vendors like Zendesk and ServiceNow, creating a more intelligent and responsive commercial ecosystem.

Other high-impact use cases gaining traction include AI-supported customer targeting, churn prediction models, and intelligent sales forecasting. The common thread is a move towards proactive, data-driven operations that allow commercial teams to do more with less.

From Implementation to Impact: Measuring Success

For any technology to prove its worth, its impact must be measurable. According to the Alexander Group's findings, the primary Key Performance Indicator (KPI) for AI implementation across sales organizations is operational efficiency. This isn't a vague goal but a collection of hard metrics, including the volume of outbound sales activities, the speed of response to inbound leads, the percentage of time reps spend on strategic selling versus administrative tasks, and the throughput rate of service tickets.

This focus on efficiency aligns with findings from across the consulting industry. Research from firms like McKinsey & Company and Deloitte consistently shows a strong correlation between AI maturity and superior business performance. The economic potential is staggering, with some analyses suggesting generative AI alone could add trillions of dollars to the global economy through enhanced productivity and innovation. By automating routine tasks, AI allows sales and service professionals to operate at the top of their license, focusing their energy on high-value activities that require uniquely human skills.

However, quantifying the return on investment (ROI) remains a significant challenge. While measuring cost savings from automation is relatively straightforward, calculating the revenue impact of improved customer engagement or faster innovation is more complex, often requiring sophisticated attribution models and a long-term perspective.

The Enduring Value of the Human Touch

Despite the powerful push toward automation, the research delivers a crucial and nuanced message: technology alone is not the answer. The most successful AI strategies are those that create a seamless partnership between machine efficiency and human empathy. Higgins emphasized this point, stating, “Despite its clear benefits and efficiencies, AI can’t do everything—customers still want human interaction. Human touch endures.”

This highlights a growing understanding that the future of customer engagement is a hybrid model. AI is best suited to handle high-volume, repetitive tasks, provide instant data analysis, and manage initial customer queries. This frees up human agents to focus on complex problem-solving, navigate emotionally charged conversations, and build lasting customer relationships. Leading companies are not aiming to replace their workforce but to augment it, creating a team of 'super-agents' empowered with AI-driven insights.

Best practices for this human-AI synergy are emerging. They include ensuring a seamless, context-aware handoff from a chatbot to a human, providing customers with the choice of their preferred interaction channel, and being transparent about when they are communicating with an AI. “Leaders must research and design solutions with adoption in mind and align use-cases with workflows,” Higgins advised. Ultimately, the greatest competitive advantage will be found not in choosing between automation and people, but in mastering the art of integrating them into a single, cohesive customer experience strategy that leverages the distinct strengths of both.