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What An MBA Didn’t Teach You About Sales

The sales profession is challenging. You need to work hard at it to succeed. You need to learn from the best. You need to improve your skills continuously. If you think you can sell since you are a hit at parties and have a lot of friends, you may soon find that you are a failure as a salesperson. Blunt truth:

because the sales profession is so hard, you have to focus on doing everything in sales very well, or you will be considered a failure.

I call this blog, Skinned Knees because I try to relate all of the learning that I have done over the past 4+ decades (while skinning my knees in the learning process).

I hope that you learn from my mistakes so that your business will grow!

AI Sales Automation: Why Your Chatbot Is Not a Sales Process

Imagine preparing for an important customer meeting. You open your favorite AI assistant, give it the prospect’s name, and ask for a summary of the company’s business challenges and the questions you should ask. Within seconds, you receive a beautifully written briefing. The assistant identifies potential operational problems, competitive pressures, and several opportunities to demonstrate the value of your solution.

There’s just one problem. One of those impressive insights concerns an acquisition the prospect supposedly completed last year.

Except the acquisition never happened.

The artificial intelligence fabricated a plausible business event and presented it as fact. Had you trusted the briefing, you might have opened your meeting with a question that immediately damaged your credibility.

This scenario illustrates a much larger problem with how B2B sales organizations use AI.

We’re asking artificial intelligence to perform too many different kinds of work without distinguishing which tasks require intelligence and which require reliable execution.

That distinction matters more than the sophistication of the AI model you choose.

The Problem Isn’t Just Hallucinations. It’s Process Design.

Salespeople increasingly rely on ChatGPT, Claude, Gemini, and other Generative AI applications to prepare for meetings, research prospects, write follow-up messages, and analyze opportunities. Those are legitimate applications of AI. In fact, I’d question why a salesperson with access to these capabilities wouldn’t use them. But consider what happens before the salesperson receives a useful answer.

They retrieve information from their CRM, gather previous meeting notes, identify stakeholders, check pricing, and reconstruct details from previous conversations. They paste everything into their AI assistant, ask a question, verify the response, and correct any mistakes.

Tomorrow, they repeat the process for another customer.

The AI may have improved the quality of their analysis, but the underlying sales process remains largely manual.

When twenty salespeople independently reconstruct the same process every day, you don’t have an AI adoption problem. You have a sales management problem.

You’re paying experienced professionals to repeatedly assemble information that your existing systems should already provide.

The solution isn’t necessarily better prompting. It’s better workflow design.

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Your Sales Compensation Plan Is Quietly Managing Your Sales Team

A salesperson reaches the final week of the quarter with a major opportunity ready to close. Legal has approved the agreement. The customer is prepared to move forward but asks for a 15 percent discount.

The salesperson understands what the discount does to margin. So does the sales manager. Finance knows as well. Yet the salesperson is measured on revenue, the manager needs the deal to make the quarterly forecast, and neither is directly rewarded for protecting margin.

The discount is approved. The deal closes. The commission increases. Everyone celebrates.

The company may have just paid someone extra to give away its profit.

No one acted dishonestly. The compensation plan worked precisely as designed. That is the problem.

Compensation Is a Management System

Most companies treat sales compensation as an administrative process. Leadership creates a plan, finance calculates payments, and managers resolve disputes when the numbers do not match expectations.

That view misses the strategic role compensation plays.

A compensation plan influences which customers salespeople pursue, how aggressively they discount, whether they favor one-year or multi-year agreements, how they collaborate, and whether they prioritize new business, renewals, margin, or market share.

What the company pays for will eventually outweigh what its leaders say they value.

Many sales leaders inherited plans that accumulated years of exceptions, temporary accelerators, regional variations, product overlays, split-credit rules, and special arrangements. The resulting spreadsheet may be technically functional while being strategically incoherent.

The warning signs are familiar:

Salespeople maintain private spreadsheets because they do not trust their commission statements.

Managers spend time resolving payout disputes instead of coaching pipeline.

Quotas are created by adding a percentage to last year’s number rather than analyzing territory potential.

A handful of top performers benefit from every contest while most of the team decides the competition is irrelevant.

These are not motivation problems. They are design problems that consume selling time, reduce margin, and erode trust.

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AI Will Not Fix Sales Problems Built on Fragmented CRM Data

Most sales leaders are asking the wrong question about artificial intelligence.

They ask which AI tool to buy, which platform has the best features, which automation will save the most time, or which sales technology will help their reps move faster. Those questions matter, but they are downstream from the real issue.

The more important question is: Does your CRM provide AI with enough trusted context to make useful recommendations?

If the answer is no, the next tool will not solve the problem. It will accelerate the confusion.

AI cannot reason well from fractured data. If account history lives in email, proposal tools, LinkedIn messages, spreadsheets, call notes, support tickets, and half-completed CRM fields, the AI is not operating from a complete commercial picture. It is guessing from fragments. A faster guess is still a guess.

That is why the CRM must evolve from a passive system of record into an active system of action. The old CRM was built to store yesterday’s activity. The modern CRM has to help shape tomorrow’s decisions.

A strong CRM foundation gives sellers a complete account context before a call. It helps managers understand pipeline risk without relying only on rep opinion. It allows AI to recommend next steps because the recommendation is grounded in actual customer history, not generic sales theory. It gives the organization leverage because the patterns learned in one deal can improve the next similar deal.

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Value Selling at Scale: AI-Driven Qualification and Sales Management Strategies

In many B2B organizations, the marketing team generates a healthy stream of incoming leads, but the sales team struggles to keep pace. The result: qualified opportunities go cold, revenue generation stalls, and business acumen around lead management erodes. This is often caused by what I call the “qualification bottleneck”: when sales management and sales processes are built for humans only, operational rhythm fractures under modern buyer expectations.

When a buyer visits your pricing page at 11 p.m. on a Sunday and your sales team doesn’t respond until mid-week, the damage is done. You’ve lost not only speed but strategic context. Your sales rep begins the conversation asking basics again, instead of starting the strategic consultative discussion your solution demands.

The remedy is a hybrid sales model: humans amplified by artificial intelligence. AI handles initial qualification via intelligent chatbots and forms that follow a structured framework such as MEDDPICCC. These systems ask the key discovery questions automatically, capture metrics, identify decision-makers, uncover timelines, goals, champions, competition, paper process — and deliver a richer lead profile to your sales team. With that strategic foundation in place, your reps can start where value selling begins: at the business case. Shorter cycles. Higher conversion. Stronger revenue management.

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