Humans and AI: Finding the Balance

AI Transforms Professional Services: Insights from Industry Experts

Amolino AI gathered revenue operations experts to discuss how AI changes professional services. Here's what they shared.

The YouTube Experiment That Cut Support Costs

Kuldeep Hillyer from Kugamon found unexpected success through YouTube videos. His team created videos for their Salesforce CPQ documentation and saw immediate results.

"We had a lot of documentation. I asked someone on our customer success team to put videos behind the documentation and put it on YouTube. Our support case count went to zero because people figured it out themselves. Then our prospects viewed the videos, so our sales cycle dropped," explained Kuldeep.

His team now integrates videos directly into their app interface. "Now if you type 'create a quote from an opportunity' on YouTube, a Kugamon video is likely in the top three results."

Creating Real-World Moments

Greta Remington demonstrated the power of in-person events. For an artisan bakery platform, her team hosted "cake picnics" that generated over 1,000 responses and sold 150 tickets in 48 hours.

"If you have long conversion lags, create a moment," Greta advised. "The longer it goes between awareness and conversion, that drops off."

AI in Revenue Operations: Current Limitations

Kuldeep, who has spent 16 years running Kugamon, highlighted where AI falls short in revenue operations.

"I've been looking at how to bring AI to make operations more efficient. What I'm finding is that at a certain size, there isn't an AI app to make life better. There's a lot of AI tools for getting prospects and data enrichment. But when a sales rep needs to create a quote, there's no AI app saying, 'Create a quote that's profitable but competitive.' That doesn't exist yet."

He added, "There is automation - sending reminders, renewals, past due notices. But having AI deal with math that you could just drop in doesn't exist yet."

Commoditizing Cognitive Skills

Vernon Keenan, enterprise AI analyst specializing in the Salesforce ecosystem, described how AI is democratizing consulting expertise.

"Many skills within consulting can be commoditized. You can take skills like requirements analysis and other cognitive skills that came from consultants that used to be a rarefied quantity. You had to pay that McKinsey guy $2,000 an hour to hear his wisdom. What happens when you get that $250-an-hour guy with a chatbot that's as good as the McKinsey guy?"

Vernon added, "The royal nature of these consultancies is going to be attacked. They're fat targets."

AI's Impact on Pricing Models

Omar Youssef addressed how AI affects service pricing: "Pricing is a big deal. When people talk about these trillion-dollar markets, they're assuming people will pay AI agents exactly what they paid humans. That's hogwash. If an AI agent does a human job, people expect the AI discount right there. You'll be lucky to capture 50% of that value with your new agent."

He sees this as positive: "There's going to be downward pressure. Hopefully that's part of the abundance equation we're after with AI. The idea is to make everything cheaper and more abundant so we can use it more. This is what people call the Jevons Paradox - once cost goes down, there's more utility."

AI as the Junior Team Member

Greta compared AI to junior employees: "AI is like having a junior level employee do background research, prepare an initial quote, do about 80% of the work. You still need that director of sales to refine it, personalize it, and add intelligence on top."

Manjit Singh from Salesforce observed growing VC interest in AI-augmented service businesses: "VC has always seen service businesses as 'throw more bodies and that's how the business grows.' But now they see that if powered by agents, you drive more productivity. Ten people who were able to do five projects can now do 20 projects."

The Content Paradox

A recurring theme was how AI-generated content becomes less effective as it proliferates. Kuldeep noted, "Once AI started generating blog posts, nobody reads blogs. Once it hit LinkedIn posts, nobody read LinkedIn. For emails, there's automation, so nobody reads your emails."

Service as Software: The New Paradigm

Vernon introduced the concept of "service as software" - the commoditization of labor that operates software.

"If you look at the Salesforce DevOps sector, all those companies together make about $200 million a year. But the consulting and labor market that could be targeted by AI is around $3.6 billion. Salesforce is a $38 billion company, but consider all the services and labor that goes with that - it's much larger."

Omar expanded on this concept: "The entrepreneurial excitement is that consultants can bring new tooling and capabilities to their skill set. This would enable them to charge higher rates. It's about how much of this commoditized knowledge you can bring into your practice to create value for customers. People are still willing to pay for value."

Client Expectations and Pricing Pressure

Manjit shared that clients already expect lower costs: "I interviewed 15-20 consulting firm leaders recently. One theme was that customers are asking 'With all these AI tools, what are you doing to bring our bill rates lower? How can we go from time-and-materials to more fixed or outcome-based contracts?'"

Vernon predicted "heavy commoditization of cognitive skills" but saw opportunity: "The value will be in delivering high-quality advice to new customers who before couldn't afford McKinsey but still need that level of advice to run their $50 million manufacturing operation."

The Next Generation of Consulting

Both experts predicted dramatic shifts in how consulting firms operate. "I fully back the prediction that an AI-first consulting firm with 10 employees will produce better outputs and deliver more projects than a traditional firm with 100 people," said Vernon.

He added, "The typical consultant will be the ex-Accenture guy in his early 30s saying 'I can do much better with these tools than these guys are doing.' He'll go back to the customer with his 10-person team and say 'I've got a 12-month plan to replace that stupid Accenture three-year plan.'"

Omar noted that firms must adapt or be replaced: "It's the classic innovator's dilemma to the nth degree. These consulting companies are getting feedback from customers now. They'll either figure out ways to do it to themselves, or other people will do it to them."

Making AI Reliable for Enterprise

Manjit discussed the challenges of making AI dependable: "These agents work but they're unreliable. We need to develop a proper AgentOps toolchain with testing, monitoring, and feedback loops. In the next 12 months, I predict AI will level up from junior employee to senior engineer in some areas."

Multiple agent systems are evolving rapidly. Vernon noted, "Google just released something called Agent-to-Agent. Salesforce is part of that group - it's a set of protocols for different agents to work together. IBM has BAI for connecting different agent frameworks. ServiceNow has an Agent Registry."

Omar added caution about the current state: "I love to talk about agents, but it's good to remind people they don't work yet. We're in the classic technology J-Curve adoption cycle - you invest a lot of money, then it's not paying off, and suddenly it pays off. That's what happened with the Internet."

Tiered Pricing for AI Services

Omar explained how AI agent pricing may evolve: "If you think about a Principal/Senior Developer level agent versus an intern-level agent, the pricing cannot be the same. OpenAI has a $20 subscription and a $200 subscription because of capability differences. Some are thinking about $100,000 for a year for an AI agent, but it has to be really good."

The Human Edge

Despite AI advances, the experts identified areas where humans remain essential:

Vernon emphasized managerial skills: "It's the managerial function where old farts like me get to smirk in the background going 'I know how to do that and tell the AI how to do that.' The operational stack is being compressed, so everybody needs to understand what's happening with stakeholders. Stakeholder empathy and managerial skills will be crucial."

Manjit highlighted industry-specific expertise: "If you're building solutions for healthcare, finance, or complex domains like CPQ, you need specialists who understand nuances, compliance, and governance. You can't teach an agent that easily."

The Warning: Career Ladder Erosion

Vernon voiced serious concerns about workforce impacts: "I'm concerned about what I call the quiet erosion. When AIs do jobs that junior people used to do, we're seeing a quiet erosion in career ladders."

His research found troubling trends: "I've done econometric studies and the preliminary numbers on jobs created by AI versus jobs destroyed doesn't look good - it's 10 to 1, 5 to 1 at least. As leaders, we need to think about bringing in young people and mitigating these negative sociological effects."

Finding the Right Balance

AI is transforming professional services with mixed effects. It excels at routine tasks and scaling expertise, but humans remain essential for strategy, creativity, and trust.

Success will come to organizations that enhance human capabilities with AI rather than replacing them, while watching the broader impacts of this shift.