The best careers after an MBA in 2027, and the AI jobs worth going for

When I applied to INSEAD, I had it fixed in my head that I needed to get into consulting.

I work in AI now. I was AI Lead for computer vision at Match Group, and today I'm Head of AI at a startup in London. From where I sit, the list of jobs worth doing after an MBA looks very different from the one I had in 2023.

Consulting is still a great door. But it's not the only one anymore, and some of the best ones are new. Here's how I'd think about it if I were graduating in 2027.

Consulting is still the biggest door, but it's narrowing

Consulting still takes more MBAs than anything else at most European schools. In 2025, half of INSEAD's class went into consulting, on INSEAD's own figures. At LBS it was 40%, from its employment report.

But look closer. At INSEAD, 27% of the class were people going back to a firm they'd already worked at. Only 23% were new hires into consulting.

McKinsey, Bain and BCG say they're not hiring fewer MBAs, they're hiring different ones. They want specialists. The LBS careers director told Poets&Quants that the recruiting process has stretched from two or three weeks to several months.

So if consulting is your plan, go for it. Just make it a plan with a second option, and bring a specialism they can't train in six weeks. Mine would have been AI.

Tech is growing again

The share of MBAs going into tech jumped in 2025. At Stanford it went from 22% to 35% of the class, Poets&Quants reported. At Harvard it rose six points to 22%. At INSEAD, tech, media and telecom went from 11% to 18%.

A lot of that growth is in AI. And the AI companies aren't only hiring researchers. They're hiring people who can take the technology to a customer and make it work. That's where an MBA, especially one with a technical background, fits.

Here are the roles I'd look at.

Forward-deployed roles: the hottest job in AI right now

A forward-deployed engineer sits with the customer instead of back at headquarters. They work out the customer's real problem, build or configure the AI to solve it, and stay until it works.

Palantir invented the role well over a decade ago. Now every AI company wants them. AWS committed an initial $1 billion to a new forward-deployed unit in 2026, and LinkedIn data put the growth in demand for these roles at 42 times between 2023 and 2025, Reuters reported.

There are two kinds, and the difference matters for an MBA.

• The engineering version needs you to code. OpenAI's Forward Deployed Engineer asks for production code in Python or JavaScript and five years of engineering, for $185,000 to $300,000 plus equity in San Francisco. Anthropic's in London asks for strong Python and pays £225,000 to £255,000.
• The strategy version doesn't. Palantir's Deployment Strategist lists coding only as a plus. You work out the customer's problem, work with the engineers, run training and present to executives. Palantir's US range is $110,000 to $170,000 base, plus stock.

If you were an engineer before the MBA, this is the job I'd look at first. It's the closest thing there is to consulting, except you're also the one who builds the answer. And remember what I said about your career before shaping your career after. This is the role where an engineering background is an advantage, not something to explain away.

Deployment leads and AI deployment managers

The more senior, less technical version of the same idea. OpenAI's Deployment Lead turns a customer's business goals into a technical plan and runs the engineers who deliver it, for $230,000 to $294,000 in San Francisco. It asks for seven years of leading customer-facing technical delivery.

That's a consulting-shaped job inside an AI company. If you've spent years leading projects with clients, this is where you'd fit.

Applied AI and solutions architects

These people sit between the sales team and the engineers. They design how a customer will use the product and prove it works.

Anthropic has dozens of Applied AI roles open. Its Applied AI Architect pays $240,000 to $315,000 in the US and £165,000 to £190,000 in London, and asks for five years as a solutions architect, sales engineer or technical account manager.

Again, the pattern is the same. They want people who've done something close to it before. The MBA gets you the business side. Your previous career has to bring the rest.

Account executives and AI sales

People underestimate sales. Account executives sell the product to companies and own the relationship, and at an AI company they're paid like it.

Their pay is quoted as OTE, on-target earnings: base pay plus commission if you hit your target. Anthropic's Mid-Market Account Executive is $290,000 to $360,000 OTE in San Francisco or New York. Its enterprise roles in London run from £195,000 to £330,000 OTE.

Here's the blunt part. None of these postings ask for an MBA. They ask for years of enterprise sales. If you've sold before, an MBA plus AI fluency makes you a strong candidate. If you've never sold, this is a much harder jump than it looks.

Strategy, operations and corporate development

This is where AI companies do ask for MBAs by name. Anthropic's go-to-market strategy and operations roles say "MBA or advanced degree preferred", and pay $270,000 to $310,000. Its finance and strategy roles and its corporate development team ask for the same.

These jobs plan how the company grows: which markets, which customers, which deals. If you came from consulting, banking or a strategy team, this is the most natural home for you in AI.

Product management

The classic MBA-into-tech job, and AI product managers are among the best paid people in the industry. OpenAI's product manager roles range from about $266,000 to $530,000, and Anthropic's Claude product manager role pays $385,000 to $460,000.

But they're senior. Anthropic's asks for eight years of experience. If you're aiming for AI product, look for the associate or earlier-career routes, and use the MBA internship to prove you can do it.

What the pay figures mean

All the ranges above come from the companies' own job postings as of October 2026, and most are for San Francisco, New York or London. They change all the time, so treat them as a sense of scale.

For comparison, the median starting base for Wharton's 2025 class was $190,000 in consulting and $164,250 in tech, on its own report. INSEAD's median was €106,100 in consulting and €94,600 in tech.

How to choose

Go back to your career before the MBA. It's your biggest asset, and it decides which of these doors are open to you.

• Engineer or data person. Forward-deployed roles, applied AI, AI product.
• Consultant. Deployment lead, AI strategy and operations, or back into consulting with an AI specialism.
• Banker or finance. Corporate development at AI companies, private equity, AI-focused investing.
• Already sold something. AI account executive roles, where commission can take the pay well past most of this list.

How to get one of these jobs

Don't blanket apply. Make a list of the fifty companies you'd most want to join, and for each one the specific role. Then find three people at each: a recruiter, or someone already doing the job.

Fifty companies, three people each, is a hundred and fifty people who have a real reason to reply to you. Ask them for advice, not for the job. How did they get the role, what does it look like day to day, what would they do in your position.

Once you understand what the team needs, tell them how your background fits, and ask if they'd refer you. That's how a cold application turns into a warm one.

Do this now

Pick two of the roles above that fit your career before the MBA. Find five people on LinkedIn doing each one, and read their profiles.

Look at what they did before the job. If it looks like what you're doing now, you've found your path. If it doesn't, you've found the gap you need to close before you apply.