Yes, I’ll do it. Love to!

And with those few words, one thought came to mind: What did I just do?

I had committed to teaching AI in marketing to a group of senior leaders at a Key Executive Master Class next October.

Now, the person who asked me to teach this class really wanted my wife to do it. Fair enough. She is more of the AI expert in our house.

But she was unavailable because she would be attending an AI Leadership Conference on the same dates. So, I offered to be second string.

My ego liked the idea. Then reality hit.

Or more accurately, fear hit.

What if I do not know enough?
What if my skills are out of date?
What if the students know more than I do?
What if I am not qualified to teach this?

Yes, this was imposter syndrome. Which is ridiculous because I have already taught courses on AI and marketing. I use AI every day. And I have helped clients think through AI, content, sales enablement, and marketing strategy.

But still, I knew the truth: my skills are not where I want them to be.

Then I remembered something important: I do not have to know everything AI can do. AI already knows that. My job is to ask better questions.

Reality check! AI can teach you AI

The right response to feeling behind is not to hide, fake it, or wait until you feel ready. The right response is to use AI to identify your gaps.

So, instead of thinking about what to teach, I asked ChatGPT “What has changed in AI over the last year?” More specifically:

• What can ChatGPT do now that it could not do a year ago?
• How about Claude?
• How have best practices changed?
• What are business users still getting wrong?
• What should marketers know now?
• What should staffing leaders know now?

A lot has changed in a year

A year ago, AI was mostly an answer engine. We used AI mostly to answer questions, write drafts, summarize documents, brainstorm ideas, and create content.

Best practices were heavily focused on better prompting. Users had to provide lots of context manually. Most work required close supervision.

AI was helpful, but it often felt like working with a smart intern. You had to break complex work into small steps. You had to fact-check everything.

The big skill was learning how to prompt. And provide the right context.

Now AI is becoming a work engine

The latest versions of ChatGPT and Claude can reason through complex problems. They can work with larger amounts of context and connect to company knowledge and files.

AI can create, edit, analyze, and organize work products. It can support multi-step workflows. And it can act like a strategist, analyst, project assistant, coder, content partner, or sales enablement resource.

The user’s job is shifting from “prompt writer” to “AI manager.” The new skill is not just asking better questions. It is designing better workflows.

Today, learning how to manage AI like supervising a very capable, very fast, very literal team member.

The critical shift: Prompting to managing

Don’t get me wrong. Prompting still matters. But prompting is no longer the whole game. The bigger skill is learning how to give AI – the right role, context, objective, and constraints. Provide the right source material, examples of success, and process for evaluating results.

And with AI, you can ask it to help you gather all these things. You can even ask it what it needs to know…and have it interview you for answers.

Staffing leader application:

If you wanted to create a new marketing plan for your company, you would not simply tell your marketing creator to “create a new campaign.” You get far better results by saying:

• Here is the audience.
• Here is the problem we solve.
• Here is the offer.
• Here is the tone.
• Here are examples of what good looks like.
• Here is the outcome we need.
• Here is how we will measure success.

AI works the same way. It did not eliminate the need for your expertise. It increases the value of your leadership.

Creating an AI in marketing master class

Once I stopped worrying about whether I knew everything, I changed the assignment. The goal was not “teach the latest best practices in AI.” The goal was to help executives understand how to use AI to improve marketing performance.

My course-building process:

I already had a strong framework from all the content I’ve created for SMART IDEAS and other Haley Marketing resources. The question became: How can AI help implement the major concepts and frameworks we teach?

Instead of starting with AI tools, I could start with business outcomes. How could I use AI to:

• Define or refine an ideal customer profile.
• Analyze buyer pain points and objections.
• Improve your positioning and differentiation.
• Analyze website design and SEO performance.
• Create better primary and secondary offers.
• Build sales enablement tools.
• Create buyer enablement content.
• Map nurturing sequences.
• Identify marketing-process leaks and sales-process leaks.
• Create a 90-day marketing action plan.

My big A-HA… The class does not need to be about AI tricks. It needs to be about using AI to solve real business problems.

Why this matters to staffing companies

Most staffing companies are underusing AI. Not because they are lazy. Because they are overwhelmed.

You know AI matters. You know the tools are changing. You know competitors are experimenting. But do you know where to start?

Today, the most successful staffing companies are using AI as a growth accelerator:

Bullhorn reported that staffing firms using AI were twice as likely to report revenue growth, and that AI adoption could save recruiters up to 17 hours per week, including time saved on candidate matching.

The State of Staffing report found that 61% of staffing firms were already using AI for business applications in 2025, up from 48% in 2024.

Meanwhile, broader business adoption is also accelerating. McKinsey’s State of AI survey reports that companies are increasingly focused on redesigning workflows, not just experimenting with tools.

For staffing firms, that is the real opportunity. Use AI to evaluate and improve every part of your operations. Sure, you can use AI to write better job descriptions and emails, but here are a few more ideas (and yes, AI helped me with this list!):

Using AI in Sales

Pre-call prospect research and account strategy. Before calling a prospect, a salesperson can ask AI to review the company’s website, LinkedIn profile, recent news, job postings, industry trends, and competitor hiring activity.

Proposal follow-up and stalled-deal recovery. AI can help salespeople create better follow-up strategies after a proposal is sent, especially when the prospect goes silent.

Skill marketing. AI can turn a resume or Indeed profile into a client-ready brief that promotes your top talent more effectively.

Using AI in Recruiting

Candidate matching and intake alignment. AI can compare a job order against resumes, applications, screening notes, and recruiter comments to identify best-fit candidates and explain why they match.

Recruiter productivity and candidate communication. AI can analyze ATS data to determine when to reach out to candidates and what to say. It can automatically send personalized, relevant email and text messages to improve service, re-engage talent, extend assignments, and ensure a more personalized candidate experience.

Using AI in Account Management

Client health monitoring and retention risk. AI can review account activity, order volume, fill rates, service issues, response times, satisfaction notes, and even call history to flag accounts that may be at risk.

Quarterly business reviews and value reporting. AI can help account managers turn performance data into client-facing reports that prove value.

Using AI in Back Office Operations

Job order, assignment, and compliance workflow support. AI can help identify missing information, incomplete records, inconsistent job order details, expiring credentials, or compliance gaps before they become problems.

Internal knowledge and process assistance. AI can act as an internal operations assistant that helps employees find policies, follow procedures, answer common questions, and complete routine tasks faster.

The new AI best practice: Ask bigger, better business questions

Most people ask AI for tasks. Better users ask AI to help solve problems.

Forget the “write me a blog post” or “create a sales email.” Instead ask your AI partner to help you with your toughest challenges.

• Where is our sales process leaking, and what should we fix first?
• How can we reposition our staffing service to appeal to CFOs?
• What objections are preventing employers from responding to our proposal?
• What content would help a skeptical manufacturing executive trust us?
• How can we turn our best sales conversations into a 90-day marketing campaign?
• What would a better buyer enablement process look like for employers who are not ready to talk to sales?

Beyond asking questions, you can ask AI to identify trends in data. Ask it to analyze your Google Analytics and identify opportunities for improvement. Ask it to review Zoom transcripts and critique your sales calls. Ask it to look at your financial statements and point out areas of concern.

The real lesson from imposter syndrome

For me, the irony in this story is that the fear of outdated knowledge became the best reason to update my skills and use AI more effectively.

AI did not make me instantly smarter. It helped me ask better questions. Identify my gaps. Organize what I knew. It helped me connect current AI capabilities to a practical business framework.

And that may be the biggest lesson for staffing leaders. You do not have to become an AI expert before you start. You have to become better at using AI to learn, think, plan, and execute.