Productivity Without Limits: How Leading Companies Are Ushering in a New Era of Digital Labor With AI Agents
The agentic AI revolution is here, and one thing is clear—if you’re not leading, you’re trailing. Companies like Wiley and OpenTable are rewriting the rules of their industries with autonomous AI agents that don’t just assist workers but analyze, strategize and carry out tasks.
As they demonstrate, AI success hinges on whether you rewrite the rules of your industry, or follow those who do.
Education publisher Wiley is using AI to onboard customer service representatives 50% faster. Wiley’s implementation of Agentforce (the digital labor platform for deploying autonomous AI agents across any business function) has improved case resolution by 40% over its old chatbot in just the first few weeks. AI agents triage registration and payment issues, directing students to resources and reducing service rep workloads.
OpenTable, seating 1.7 billion diners annually, uses AI agents to handle reservation changes and loyalty points, freeing up employees to focus on building customer relationships. Just saving two minutes per call creates massive efficiency.
At Salesforce, the help site sees over 60 million visits a year, and with Agentforce, 83% of queries are resolved without any human involvement. In just a few weeks, Agentforce doubled its capacity, handling 32,000 automated conversations.
These agents represent a new era of digital labor that orchestrates and carries out high-value, multistep tasks. And they never stop working. It will usher in a wave of productivity and innovation that’s not limited by what humans alone can accomplish.
Leading companies are supercharging their employees’ capabilities, and creating a new era of abundance. AI agents work around the clock, creating plans, solving problems and delivering efficiency and productivity.
How can you empower your workforce for the next wave of AI, and build a digital workforce, with minimal pain and maximum gain? Here’s the good news: you don’t need to spend months or millions training your own large language model (LLM) or building from scratch.
LLMs, while powerful, are just one piece of the puzzle. Real enterprise AI success, as Wiley, OpenTable and Saks have found, comes from integrating data, AI and automation. This allows AI to not only answer questions and generate text (now table stakes) but actually perform work for you.
LLMs cannot take action. They can only respond to questions, which means it will never get AI to do actual work. Businesses need an AI system like Agentforce, where agents are woven into company data, business processes and everyday workflows, working alongside humans. All of this is built into the Salesforce platform, which makes it easy for companies to quickly turn on agents. For example, Saks Fifth Avenue launched its first AI service agent in just one week.
Here are the 5 key elements that early Agentforce adopters have found essential to success:
Real-time access to quality data is crucial for successful AI. Platforms like Salesforce Data Cloud unify structured and unstructured data, connecting it to the LLM. Top platforms use techniques like retrieval augmented generation (RAG) and semantic search to surface the best data for the job.
AI agents are capable of carrying out multistep, complex tasks, like initiating a return for a shopper and reordering a different item. Central to this is a reasoning engine, which generates a plan based on what a user is trying to do. It evaluates and refines the plan, pulling data from CRM and other systems. It decides what business process to use based on the request, and repeats the process until it’s right.
Because they can take action with little human intervention, AI agents must have built-in security guardrails. The agent has to “know” what it can and cannot do. If a requested task seems outside the organization’s guardrails, or the agent cannot access the right data to do the job, it needs to understand that and hand it off to a human. These guardrails also encompass strong permission rules around who can access and share data.
Generative AI shines at answering questions and creating content, but its true potential lies in taking action through business workflows. Salesforce’s Flow automates tasks, and MuleSoft APIs connect systems, enabling AI agents to manage processes like fraud detection—flagging suspicious activity, alerting customers, canceling cards, initiating replacements and updating cases across your business.
AI agents and employees will work collaboratively, using their unique strengths to achieve more than either could on their own. Agents process huge amounts of data, and execute complex tasks, while humans bring strategic thinking, emotional intelligence, wisdom and judgment. This partnership will redefine workflows in all industries, leading to faster, smarter decision-making.
Many businesses believe training an LLM with their own data will create a model that knows everything about their business and customers. However, LLM training is expensive and time-consuming, and requires specialists. For most companies, it’s not feasible.
Even if you could train your own LLM, it wouldn’t stay accurate for long. It only knows what it’s trained on, so any updates—like a changed customer record—make it outdated. It’s like a GPS that works until the first detour. When the route changes, you must reboot the system—that’s the reality of training your own LLM.
Many companies are stuck in the pilot phase with AI, because of data quality issues, trouble identifying use cases and because many believe it can’t execute more sophisticated tasks.
Leading companies like Wiley and OpenTable know there is little value in building something from scratch. Using out-of-the-box AI tools, a broader system of data flows, automation and workflow integration, is the key to delivering a better customer experience, building a digital labor force and grabbing a piece of that trillion-dollar AI pie.
By Patrick Stokes, EVP of Product and Industries Marketing, Salesforce.
