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December 18, 2025

Inbenta AI Appoints Channel Veteran Brandon Pineda to Spearhead Aggressive Ecosystem Expansion as Head of Global Partnerships Amid Surging Demand for Production-Ready Enterprise AI

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The Complete Guide to AI Chatbots and How They Evolve Into AI Agents

AI agents have arrived. Today, more than 987 million people interact with AI chatbots, and the technology has advanced well beyond scripted, rule-based systems. Businesses are now turning toward AI agents — autonomous systems capable of taking actions, executing workflows, and delivering measurable results. The U.S. market for enterprise AI agents is projected to jump from $769.5 million in 2024 to $6.56 billion by 2030. The adoption of this technology by businesses has been rapid. Here’s a guide to start deploying AI agents successfully in your business.

Businesswoman using AI chatbot on smartphone while walking in a U.S. city, showcasing AI agent adoption in enterprise technology.

A group of professionals in a meeting, smiling and engaged in discussion, representing collaborative teamwork essential for successfully scaling enterprise AI agents.|Inbenta infographic slide titled "Pitfall: Fuzzy Goals," contrasting unclear tech-first experiments with solutions like defining business-driven use cases and setting measurable outcomes.|Inbenta infographic slide titled "Pitfall: No Guardrails," explaining the risks of scaling early pilots without policies and the need for governance and observability.|Inbenta infographic slide titled "Pitfall: Data All Over the Place," addressing how data silos affect AI reliability and advising investment in knowledge engineering.|Inbenta infographic slide titled "Pitfall: One-Off Prototypes," discussing the inability to scale isolated workflows and the necessity of a shared platform.|Inbenta infographic slide titled "Pitfall: No Trust," explaining that agents fail when employees lack confidence in them, and recommending change management and communication.

Top 5 pitfalls when scaling enterprise AI agents (and how to avoid them)

Enterprise AI agents are moving from concept to production across industries, but scaling them remains one of the most persistent challenges business leaders face.

A group of three business leaders in a boardroom working around a laptop computer.||How do you choose the right enterprise AI tool, between a chatbot, Agent Assist and autonomous agents|||Infographic titled “A Simple AI Agent Checklist.” Displays six steps for starting your AI journey: pick one use case, start with Agent Assist, define guardrails, set up observability, pilot with a small group, and measure and iterate for continuous improvement.|Infographic titled “How to Pick the Right Tool.” Compares Chatbots, Agent Assist, and Autonomous Agents — showing how each works, what tasks they handle, and the level of human control or autonomy involved.|Infographic titled “AI Agents: 3 Trust Pillars.” Visualizes three pillars — Architecture, Safety, and Governance — showing how modular design, guardrails, and accountability create safe, scalable AI systems for the enterprise.|Infographic illustrating five levels of AI agent maturity — from a static chatbot to a fully integrated multi-agent system. Shows progression from basic Q&A automation to agent assist, human-supervised task automation, autonomous agents with guardrails, and finally a network of coordinated enterprise agents working across systems.

What are enterprise AI agents (and how do you scale them responsibly)?

The promise of AI is already here.

No Gatekeepers, No Limits

The promise of AI is already here. Leaders need to wake up and catch up or get left behind.

Claude Gets Hacked: AI agent goes rogue

Claude Gets Hacked: AI agent goes rogue (and how to prevent it!

Hackers used “vibe-hacking” to turn Anthropic’s Claude into a cybercriminal. It highlights the importance of designing AI agents with strict guardrails, human oversight, and auditable safeguards to protect both businesses and their customers.

Salesforce and ServiceNow’s $1.5B investment in Genesys promises a seamless one-stack CX solution, but beneath the headlines lie major risks.|Salesforce and ServiceNow announce a $1.5 billion investment in Genesys

Why the $1.5B Genesys bet could backfire

Salesforce and ServiceNow’s $1.5B investment in Genesys promises a seamless one-stack CX solution, but beneath the headlines lie major risks. Vendor lock-in, overreliance on unproven AI, and one-size-fits-all capabilities could leave enterprises exposed if outcomes fall short. Cautionary examples like Klarna’s failed AI bet underscore the danger of overpromising technology. Independent platforms like Inbenta’s Programmed Intelligence offer a safer alternative: control, flexibility, and tailored CX without sacrificing trust or differentiation.

AI Insights: Why Listening Is the Hardest Skill in Business|

AI Insights: Why listening is the hardest skill in business

For Sarah Johnson, Inbenta’s Global Head of Client Success, customer success is about empathy at scale. She champions disciplined listening, cross-functional fluency, and trust as the real differentiators for growth.

|Only 5% make it in AI — and here’s how to join them.

The 5% Club no one talks about

According to a recent MIT report, 95% of GenAI pilots yield zero return. The 5% that succeed have figured something out about digital transformation in the age of AI. It’s a matter of focus, and knowing where to look.

|Inbenta CEO Melissa Solis|Inbenta CEO Melissa Solis

AI Insights: How Melissa Solis breaks barriers as a female tech entrepreneur

Inbenta CEO Melissa Solis has turned struggle into strength, showing women in AI how to lead boldly, even when there’s no seat at the table.

Inbenta CEO Melissa Solis and Head of Marketing Adam Highfill

From $300 to $610 Million: Inbenta CEO Melissa Solis on Resilience and Results

Melissa Solis, CEO of Inbenta, built a tech company with her brother Merlin from $300 to a $610 million exit. In a conversation with Adam Highfill, Head of Marketing at Inbenta, Melissa shares her journey from childhood hardship to business success and how her experiences shaped her approach to leadership and entrepreneurship.

AI Insights: Why Most Enterprise AI Fails to Scale

Despite AI being a top-three priority for 75% of executives, only 26% of companies have successfully scaled it to realize real value. In this expert-led discussion, Inbenta strategic advisor Bobby Mehta and CEO Melissa Solis explore why AI efforts often stall — from poor planning to lack of guardrails. They emphasize the need for a clear, strategic framework focused on data, governance, and execution to fully leverage the power of Generative and Agentic AI at scale.

How to drive enterprise transformation with AI: Lessons from the past, strategies for the future

As companies begin fully embracing AI, many are struggling with the state of their data, the challenge of integrating powerful new tools within their existing systems, and understanding how to measure their success. Inbenta CEO Melissa Solis recently explored these topics in a conversation with Inbenta strategic advisor and ex-TransUnion CEO, Bobby Mehta. The discussion covered common pitfalls and practical advice for businesses looking to implement AI effectively.

From API to MCP: Rethinking how AI is integrated

While several new protocols are emerging for integrating AI agents with external data and services, the Model Context Protocol (MCP) is quickly gaining traction. This article compares MCP to traditional APIs, exploring their differences, benefits, and real-world applications for businesses looking to scale AI capabilities with less complexity.

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