Ashley Gross’ Post

ZoomInfo vs. Apollo vs. AI Sales Intelligence: What's Actually Different? Learn how these approaches differ in contact data, account intelligence, prospecting, AI research and sales engagement.

Here's the counterintuitive truth about AI-powered prospecting that most RIAs miss: Automation multiplies whatever selection logic you give it. If your ICP is fuzzy, your qualification signals are vague, or your target criteria aren't clearly defined-automation doesn't fix that. It scales it. You end up with a calendar full of meetings that waste your time and your team's energy. The advisors seeing real results from AI prospecting aren't automating first and debugging later. They're getting the sequence right: 1. Define your actual Ideal Client Profile (not your wishlist) 2. Build clear qualification signals 3. Set up the process logic 4. Then automate at scale When you reverse that order, you're not generating better prospects; you're just generating more noise. Your prospect quality problem isn't a technology problem. It's a selection problem. And selection comes before automation, every time. The advisors we work with typically see a 3-4x improvement in qualified conversations per month once they fix the selection logic first. It's not because the AI got smarter. It's because the system is finally working on the right targets.

AI can do a lot in sales. But I don’t think its best use is sending hundreds or thousands of automated LinkedIn messages and calling it prospecting. For me, the real value is in helping a salesperson do the basics better. Finding and researching the right prospects. Building a picture around a target account. Looking at recent news, developments, growth, new contracts, new locations or changes within the business. Giving you a genuine reason to pick up the phone. And then there’s follow-up. We’ve all had those weeks where one or two things completely take over. You tell yourself: “I’ll follow that up tomorrow.” Tomorrow becomes Friday. Friday becomes next week. And suddenly that quieter prospect you meant to speak to hasn’t heard from you for two weeks. That’s where AI can be genuinely useful. Bring the opportunity back to the top of your list. Remind you why you were meant to follow it up. Show you what’s changed since you last spoke. Maybe even prepare a draft email or suggest a reason to make the call. Not replacing the salesperson. Making sure the salesperson has the right information, at the right time, and doesn’t let good opportunities quietly disappear. There are plenty of AI tools promising: “Give us your target market, and we’ll find the leads and do the outreach for you.” Personally, that’s the bit I’m least interested in. I’d much rather use AI to understand 20 good prospects properly than send a generic message to 2,000. Because when you eventually pick up the phone, the quality of what you know still matters.

The next competitive advantage in B2B sales won’t be sending more messages. It will be knowing which conversations are worth having. AI is changing the economics of prospecting. Imagine combining LinkedIn’s professional network with an AI assistant like Claude to research accounts, analyze publicly available information, identify relevant prospects, and prepare personalized outreach at scale. The opportunity goes far beyond automation. → From volume to relevance: Prioritize prospects based on fit, intent, and business context. → From generic to personalized: Build outreach around a prospect’s role, challenges, and company priorities. → From activity to outcomes: Give sales teams more time to qualify opportunities, build relationships, and close deals. But there’s an important distinction: AI-assisted sales is not automatically autonomous sales. Integrations, permissions, data quality, platform rules, and human oversight determine what can actually be automated. And the real risk? Automating a weak sales process only helps you make the wrong moves faster. The winning model is not AI replacing salespeople. It’s sales professionals using AI to operate with greater precision, speed, and strategic focus. My takeaway: The future belongs to sales teams that combine machine efficiency with human judgment—not those that simply send the most messages. One question for sales leaders: Are you measuring your team’s activity, or the quality of the opportunities that activity creates? #ArtificialIntelligence #B2BSales #SalesLeadership #SalesAutomation #AgenticAI #LinkedIn #RevenueOperations #DigitalTransformation

Lead lists are easy to buy. A real reason for a prospect to talk is harder to find. Intent-driven sales is gaining traction as teams look beyond broad lists and toward people actively researching a solution. But a technology trend isn’t a go-to-market strategy by itself. Start with the costly friction: Are reps spending time on contacts who aren’t in-market? Are interested prospects being reached too late? Then validate whether better timing and verified data actually improve pipeline outcomes. If the problem isn’t urgent enough for a buyer to pay to solve, better AI won’t fix the fit. At LeadConnect Pro, we help businesses identify prospects earlier while they’re searching. Our Quality Guarantee is straightforward: if the data isn’t verified, you don’t pay. Build around the customer’s problem first; let technology support the solution. What sales problem are you seeing teams most willing to invest in solving right now? #B2BSales #GoToMarket #IntentData #AI

67% of B2B buyers say they'd rather not talk to a sales rep. Yet 69% turn to one to validate what AI told them. That gap, from Gartners 2026 buyer research, is one of the most important numbers in professional services marketing right now. Clients/Prospects want to do the work themselves. Then they want a trusted human to tell them they got it right. At the same time, a recent HBR piece argues that agentic AI is dissolving the line between marketing and sales. However, only about 1/3 of organizations report full sales-marketing alignment, despite a decade of investment in technology & tools. In professional services, the stakes are different. Our "sales force" is primarily partners and client-serving professionals. These individuals bring a high opportunity cost associated with their time. The goal isn't to turn them into pipeline managers. It's to let AI carry the continuous loop of signals, timing, and relevance, so that when a partner does inititiate as conversation, it's one worth having. AI won't replace that call. But, it can influence whether the call happens at the right moment. But, what's marketing role? My view is marketing & sales need to rethink the inside sales / business development role. It's not about sales, it's about establishing a relationship and wayfinding. The first human engagement in a digital buyer journey should not be a BANT, it should reflect your brand - insightful, helpful and connecting that individual seamlessly. The role is not sales, it's not marketing, it being a firm concierge - curating the client/prospect experience. Three questions you should ask your organization: → Do marketing and client-serving leaders share one growth number? → Who acts on an AI-surfaced signal, and within what time frame? → Are we measuring activity, or client confidence? The technology is ready. The operating model usually isn't. How is your firm erasing the line between marketing & sales? https://lnkd.in/g738JV8i

🚫 Everyone says cold calling is dead. I know the opposite. Cold calling didn't die. Everyone just stopped doing it. 📉 Over the last 15 years, sales teams shifted to email automation and LinkedIn outreach. Now those channels are maturing with AI. ❌ Inboxes are overflowing. ❌ Response rates keep falling. Meanwhile — the phone has become a blue ocean. Here's the interesting part: 🤖 AI can write your call script. 🤖 AI can research your prospect. 🤖 AI can tell you who to call. But AI still can't build trust in a live conversation. That's still human. Which means one of the oldest sales skills is quietly becoming one of the biggest competitive advantages again. The companies investing in cold calling today aren't going backward. They're moving into a channel their competitors abandoned. Question: has cold calling become more effective because it's actually less competitive?

High lead volume can make it difficult to identify genuine buying intent before opportunities slip away. Discover how AI can help prioritize, research, and qualify leads more quickly, allowing you to focus on what truly matters. @microsoft-dynamics #MicrosoftDynamics365

High lead volume can make it difficult to identify genuine buying intent before opportunities slip away. Discover how AI can help prioritize, research, and qualify leads more quickly, allowing you to focus on what truly matters. @microsoft-dynamics #MicrosoftDynamics365

High lead volume can make it difficult to identify genuine buying intent before opportunities slip away. Discover how AI can help prioritize, research, and qualify leads more quickly, allowing you to focus on what truly matters. @microsoft-dynamics #MicrosoftDynamics365