Salesforce Highlights “Last Mile” Problem in Enterprise AI Adoption
Salesforce Highlights “Last Mile” Problem in Enterprise AI Adoption
Salesforce says many businesses are still struggling to turn artificial intelligence investments into measurable financial results, despite widespread interest in adopting the technology.
Speaking during the opening of Salesforce’s Philippine office in Manila, Srini Tallapragada, the company’s President and Chief Engineering and Customer Success Officer, said the real test of AI success is simple: whether it shows up in a company’s profit and loss statement.
“Every CEO and board member wants to become an AI-driven enterprise,” Tallapragada said. “But when you ask whether AI has actually improved growth or reduced costs, many companies still don’t see the impact in their P&L.”
Salesforce refers to this gap as the “last mile problem” — the challenge of moving generative AI from experimentation to real-world enterprise use. While large language models continue to improve, deploying them inside regulated industries remains complex. Businesses must connect AI systems to internal data, comply with regulations, and ensure decisions can be audited later.
To address these challenges, Salesforce developed Agentforce, a platform designed to link AI models with company systems while maintaining compliance and reducing errors. The platform has grown rapidly, generating over $800 million in annual recurring revenue and supporting thousands of active customers.
The company is also increasing its investment in the Philippines, which Salesforce sees as one of its fastest-growing markets in Southeast Asia. According to Abraham Cuevas, Salesforce Philippines’ regional vice president and country manager, local industries such as BPO, banking, telecommunications, and healthcare are exploring AI to improve efficiency and modernize operations.
One example cited by Salesforce is healthcare provider Maxicare Healthcare Corporation, which used Agentforce to automate approval processes for dental service authorizations. The change reduced administrative costs while maintaining existing workflow systems.
Tallapragada noted that although companies worldwide have invested heavily in AI infrastructure, many are still searching for ways to translate that investment into measurable business results. Salesforce aims to bridge that gap by helping organizations apply AI to practical operations such as lead generation, customer service, and fraud detection.
As AI adoption continues to grow, Salesforce believes the next phase of the technology’s development will focus less on experimentation and more on delivering tangible business value.
