Salesforce: AI Boosts Customer Service in 60 Days

A Rapid Adoption of AI Agents in Customer Service

According to a survey conducted by Salesforce, an overwhelming majority of 70% of companies using AI agents for customer service see a return on investment in just 60 days. This rapid adoption is supported by a significant increase in the use of these technologies, rising from 39% to 66% within a year. This trend is further reinforced by a new results-driven pricing model, which is expected to accelerate the integration of AI in businesses even more.

The study, which surveyed 3,075 service professionals across 13 countries on five continents, reveals that the adoption of AI agents in customer service has experienced impressive growth. To maintain customer trust, 77% of companies using AI agents ensure that customers can contact human agents at any time.

The Impact of AI on Customer Services

Salesforce's survey indicates that 85% of service organizations are now using AI in various forms. Among them, 78% leverage generative AI, 71% predictive AI, and 66% agent-based AI. The use of agent-based AI is expected to reach 88% by the end of next year.

AI agents are widely adopted in customer-oriented services, with a usage rate of 89%. They are deployed throughout the service cycle and across all channels, including web, voice, apps, SMS, and social media. The main use cases include proactive outreach, personalized product recommendations, case resolution, case routing, and post-call work.

Developing Human Skills in the Age of AI

With the rise of AI agents, companies are investing in developing new skills for their employees. Roles expected to grow include data management (66%), specialists (62%), AI architects (61%), query specialists (50%), and AI generalists (48%).

To support this expansion, companies are training their employees in AI, with only 3% of service representatives not participating in upskilling programs. Training includes workshops and conferences (53%), internal training programs (53%), and online courses (49%).

The priority skills for service professionals include supervising and judging AI, solving complex problems, as well as adaptability and learning agility, which encompass strategic thinking.

Improving Productivity with AI Agents

Nearly 90% of respondents use AI for internal employee-oriented functions, such as optimal team management. Half of service leaders use AI agents to analyze trends and adjust their workflows. Service leaders utilize AI to track employee performance (50%), predict demand (47%), and recommend staffing schedule adjustments (40%).

The results of using AI for back-office performance management are very promising. An overwhelming majority of 92% of service leaders note that AI enhances their ability to coach at scale.

Measuring the Impact and Results of AI Agents

The survey reveals that 83% of service organizations with AI agents have deployments across five or more channels. AI agents are no longer limited to a single point of contact for businesses. The primary channels include email, online chat, messaging apps, SMS, and phone.

AI agent deployments include 74% for online chat, 72% for email, messaging apps, phone, and SMS, and 69% for customer portals and collaboration tools. The main challenge for AI agents is the transition to humans on any channel chosen by customers. AI agents must have contextual understanding of each engagement to properly inform their human colleagues.

The big surprise for some regarding this global survey on the adoption of AI agents is that the return on investment comes faster than companies initially anticipated. The survey revealed that 40% of the time, AI is used in case resolution, with work being done completely autonomously. This outcome could potentially lead to an average reduction of 20% in case resolution time.

Service organizations measure AI adoption based on tangible business outcome metrics, including indicators such as case resolution time. The survey found that 70% of service organizations with AI agents see measurable value within 60 days of deployment, while 25% of service organizations see value from AI agents within 30 days.

The focus is now more on business outcomes, as it should be. Lessons learned from nearly two years of commercial adoption of AI agents clearly show that technology must serve business needs for adoption to accelerate. Resolution time, more efficient workflows, the ability to anticipate outcomes, and ultimately, customer and employee satisfaction are essential for commercial success and broader deployment of AI agents.

The survey revealed that the performance indicators that have improved the most with the use of AI agents include customer satisfaction, productivity of service representatives, average handling time, and customer retention. First response time has also improved.

Salesforce has shared valuable and surprising lessons after 1 million customer conversations with AI agents, including the need for agents to have a dynamic brain and a caring heart.

Now that Salesforce has ramped up the use of AI agents, other lessons need to be shared, including the emphasis on ease of deployment and better alignment of goals aimed at maximizing outcomes rather than merely maximizing symbolic usage. Salesforce's focus on evaluating AI agents based on business outcomes has materialized with the introduction of a help agent, a pre-packaged service agent designed to deliver faster value to businesses.

The help agent is connected to a company's knowledge base, workflows, and sanctioned actions in just a few minutes. But innovation goes beyond mere ease of deployment; it also concerns how customers can truly measure the return on their investments in agent-based AI. The pricing model for the help agent is based on pay-per-resolution. This results-driven pricing model means that companies only pay when the AI agent autonomously resolves an issue, without human intervention.

The trust needed to package innovation and pricing based on actual results comes only from millions of customer interactions and tens of thousands of customers using the help agent.