Application engineers and technical pre-sales

ISCO-08 2433, 2151

Application engineer, Pre-sales engineer, Solutions engineer, Tender engineer, Technical sales support engineer, Solution architect

AI exposure40%

Headcount need, in FTE

Exposure range

Your current headcount

FTE

Need in 203094 FTE-6 FTE (-6%)

Need in 203588 FTE-12 FTE (-12%)

How AI is used on these tasks today

Automation 71%Augmentation 29%

In AI conversations about this job's tasks: the AI does the task itself (automation) or helps the person do it (augmentation).Anthropic Economic Index, April and May 2026. Occupations: Sales Engineers. AEI

1. Exposure 40%Average automation potential of the job's tasks. Range for this family: 23 to 60%.ILO occupations used: Technical and Medical Sales Professionals (excluding ICT) (50%), Electrical Engineers (31%). ILO data

2. Strategic ceiling 100%Your call: how much of this potential do you want to capture? Nobody can set it for you.

3. Adoption speed midpoint 2030

Inherits your company stance, adjustable for this family.

4. Conversion to headcount sensitive 30%Default 30%: Faster offers let the team answer more tenders and cover more projects, so most of the gain goes into commercial coverage.

Target AI skills

level 1 to 4

Foundation

Use AI assistants every day

Frame and phrase a request

Check and challenge AI outputs

Protect data and respect the rules

Applied

Rethink one's process with AI

Analyse data with AI

Produce content with AI

Delegate to and supervise AI agents

Job skills

Growing in value

Understanding customer installations and constraints
Solution architecture for complex projects
Technical negotiation with consultants and integrators
Checking AI-generated configurations and offers
Demonstrations and proofs of concept

Losing value

Answering standard technical questions
Filling tender compliance matrices
Configuring and pricing standard solutions
Searching catalogues and datasheets

How the job will change

Application engineers spend much of their time on repetitive pre-sales work: answering technical questions from distributors, filling compliance matrices for tenders, configuring switchboards or building management systems, drafting technical offers. AI assistants trained on catalogues and past offers now handle a large part of this, and configurators produce a first bill of quantities from a specification document in minutes.

The job moves towards complex projects where standard answers fail: data centres, hospitals, industrial sites with strict continuity of supply requirements. A good application engineer tomorrow will understand the customer's installation better than the customer, spot the technical risk in every AI-generated offer, and be credible in front of consulting engineers and integrators.

2026-2027: Assistants answer standard technical questions from distributors and installers.
2028-2030: Offers and compliance matrices generated from specifications, then reviewed by engineers.
2031+: Pre-sales teams concentrate on complex projects and large accounts.

Watch out

Distributors and installers will increasingly get standard answers straight from AI tools. Before replacing a departure in a junior support role, check how much simple demand is actually left. See the seniority outlook below.

What if you hired fewer juniors?

Your 2036 seniors are the juniors you hire today.

Seniors available in 2036-5%2 FTE short

Gap above 5% from2036

Your seniority mix today

Juniors (0 to 3 yrs in the profession)25%Seniors (10+ yrs)30%

Mid-level (3 to 10 yrs in the profession, the remainder)45%

Cut in junior hiring -40%

For

Advanced settings

Juniors promoted each year25%Juniors leaving each year12%Senior gap filled by external hiring0%If every company makes the same bet, senior profiles will be scarce and expensive.

Seniority mix, % of today's headcount

Juniors25%Mid-level42%Seniors28%

2026 2036

Free guide

The AI Cookbook 2026

albert's guide to cut through the noise around generative AI and turn it into workforce decisions.

What AI actually changes in jobs and skills
Why the junior pipeline matters more than most companies realise
How to integrate AI into workforce planning

Download the AI Cookbook

Run these scenarios on your actual workforce

AI Impact Diagnostic: 6 to 8 weeks, your data in albert, three costed scenarios and the projected seniority mix for each job family.

Book a call

How the numbers are built

Every headcount figure combines four assumptions. Three come pre-filled from public research and job family defaults. The strategic ceiling is yours to set.

Public researchExposureAverage automation potential of the job's tasks, from the ILO's 2025 task-level scores.

Your decisionStrategic ceilingHow much of that potential you choose to capture. Your decision, not ours.

Your companyAdoption speedHow fast your company moves, set once for the whole company.

Job family defaultConversion to headcountHow much of the productivity gain becomes fewer people rather than more output.

Headcount effect

Seniority outlook

A flow model with three levels of experience in the profession. Promotion and exit rates are set so that today's mix stays stable when hiring does not change: any gap you see comes from the junior hiring cut alone.