Are AI Agents Overhyped? Here’s How to Make Them Work For You

AI was supposed to reduce work. So, why do we feel busier than ever?

AI burnout and fatigue are real! In this episode of the Responsive Podcast, Jennifer and Sunder unpack one of the biggest questions facing today’s bid and proposal professionals: how can teams use AI for proposals, RFPs, and strategic responses without creating even more work?Together, they explore why so many proposal teams feel stretched thin, why AI hasn’t yet reduced workload, and why the reality for many teams is doing more work in less time. This conversation is built for anyone in proposal management, strategic response, sales enablement, or revenue operations who is trying to move from overwhelm to a more sustainable, strategic way of working.Jennifer and Sunder explore why teams should start with low-judgment, repetitive tasks, how to get to a first draft faster, and why a strong, trusted knowledge base is essential for better AI-generated responses. They also cover AI fluency, leadership education, go/no-go decisions, and how AI can support every phase of the pursuit lifecycle, from qualification and research to proposal development and post-submission learning. This video is all about using AI in bid management and proposal workflows to improve focus, strengthen response quality, and help teams spend more time on the work that actually drives wins.Video Chapters:00:00 - Understanding User-Centric AI Interaction08:52 - From Overwhelm to Empowerment12:52 - The Role of AI in Strategic Response16:09 - Preparing for an AI-Driven Future

Are AI Agents Overhyped? Here’s How to Make Them Work For You

If you’ve been hearing nonstop hype about AI agents but still aren’t sure what they actually do—or how to use them—this episode breaks it down. In this episode of Sit Down with Sunder, AJ Sunder (Responsive CIO & CPO) unpacks what AI agents really are, how they work, and how organizations can start using them to drive real business outcomes.Despite all the excitement around AI agents, most teams aren’t using them yet. Why? Confusion, risk, and unrealistic expectations. Sunder cuts through the noise and focuses on what actually works.What you’ll learn about AI agents:- What defines an AI agent (and what doesn’t)- Why “AI agent hype” is outpacing real adoption- How to get started with AI agents safely- The importance of human-in-the-loop workflows- When to use AI agents vs AI assistants- Common mistakes organizations make early on- How to measure ROI and business impactThe big takeaways from Sunder?- Most organizations should start with AI-assisted workflows, not full agents- The best early use cases are repeatable, auditable, low-risk tasks- AI agents require clean, centralized knowledge to work effectively- Fully autonomous agents can be risky, especially in high-stakes environments- The goal is more than just time savings. Aim for better outcomes and smarter decisionsOne standout idea: treat AI agents like new hires. You wouldn’t give a new employee a critical, irreversible task on day one, so you shouldn't do it with AI agents either. As AI continues to reshape how organizations respond to RFPs, manage knowledge, and collaborate across teams, understanding how to move beyond hype is critical. If you’re looking to turn AI agents into something practical—not theoretical—this conversation is a strong place to start.

If AI Makes Building Software Easy, Should You Build or Buy? A CIO & CPO’s Perspective

In this episode of Sit Down with Sunder, Responsive CIO & CPO AJ Sunder joins host Jennifer Cannizzaro to tackle the question teams are asking in 2026: If AI makes it easy to build software, should you actually build it…or buy it?AI-assisted coding can produce “meaningful applications in an afternoon.” But Sunder argues the real costs show up after the prototype: deployment, ownership, security, compliance, and long-term maintenance—the parts AI hasn’t made easier yet. What you’ll learn: 1. Why build vs. buy feels more urgent now than it did even 12 months ago 2. The “shiny object” trap: building is fun, but owning is hard. Governance and risk: why internal apps still create real exposure (PII, privacy, access control) 3. How to think about systems you don’t want to leave to chance (e.g., CRM, payroll, SRM) 4. A practical decision framework + scorecard to evaluate build, buy, or hybrid The framework (quick preview): Sunder’s criteria include: business criticality, user scope, integration complexity, lifecycle velocity, and data sensitivity—and a key reminder: ask these questions before you start building, because teams get emotionally attached fast. Want the full scorecard?⁠ Read the companion blog! [https://www.responsive.io/blog/build-or-buy-software-in-the-age-of-ai] About Responsive: Responsive is the AI and industry leader in Strategic Response Management (SRM), helping organizations govern knowledge and deliver trusted, winning responses at scale.

Can We Predict AI Trends for 2026? Responsive's Hottest AI Takes & Biggest Bets

Can we predict AI trends for 2026 without looking ridiculous? 😅 In this first episode of the new "Sit Down with Sunder" Responsive video series, AJ Sunder (Responsive Co-Founder and CIO) joins Jennifer Cannizzaro (VP of Product Marketing) for a candid conversation on what’s next for AI in 2026 — and what it means for bid and proposal teams doing high-stakes work every day.Sunder reminds us all that “the fastest way to look foolish is to predict the future" before getting ultra-specific and into the details of his big three AI predictions for 2026 * AI agents start working together: agent-to-agent orchestration across tools and workflows. * AI is judged by performance under pressure: less “cool demo,” more reliability, repeatability, and real-world accuracy. * Governance becomes the deciding factor at scale: AI safety moves from “nice to have” to required for adoption. Sunder also provided three rapid-fire “big bets” for leaders entering 2026: Make sure everyone has access to a baseline AI assistant.Deploy agents around core business workflows to see immediate ROI.Invest in enterprise data and a data governance strategy.Also: the most relatable AI agent example you’ll hear today involves Friday night dinner plans and why humans still want the final call. Video Chapters:00:00 [https://www.youtube.com/watch?v=jBkq_0wXDfs] - Intro + why predicting AI can make you look foolish04:17 [https://www.youtube.com/watch?v=jBkq_0wXDfs&t=257s] - Prediction 1 — Agent-to-agent ecosystems06:30 [https://www.youtube.com/watch?v=jBkq_0wXDfs&t=390s] - Prediction 2 — AI engineering maturity + RAG12:40 [https://www.youtube.com/watch?v=jBkq_0wXDfs&t=760s] - Prediction 3 — AI Trust and AI safety19:20 [https://www.youtube.com/watch?v=jBkq_0wXDfs&t=1160s] - Rapid-fire — the three big bets for 2026

How CAPTRUST Scaled RFPs: 15 Teams, 70 SMEs, and AI with a Human Touch

In this episode of The Responsive Podcast, Joe Kopyt (Responsive) interviews Megan Cutter (CAPTRUST), who shares her journey into the world of RFP management and knowledge management. Megan discusses the evolution of her team, both before and after the introduction of AI, and the importance of technology and collaboration with subject matter experts, particularly in terms of how a single central member can play a crucial role. Megan highlights the role of AI in enhancing CAPTRUST’s RFP processes while still retaining the crucial element of human touch during the writing and review process. This episode also highlights the importance of communication between teams, the importance of building trust in AI and automation, and the evolving future of proposal management.