netzstrategen AI Operations Self-Check
AI Operations Self-Check by netzstrategen
How much potential does AI Operations have for your company?
The Self-Check is based on studies and on more than 30 of our own projects with mid-sized companies in the DACH region. The result puts a figure on the range of your savings and revenue potential.
Based on studies By industry and role
From which perspective would you like to start?
Choose the role that fits you best. The check starts straight away, and both the questions and the result follow your choice.
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Based on studies
We calculate with figures from BCG, McKinsey, Gartner, MIT, VDMA and PwC.
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Potential in euros
Savings and additional revenue are shown separately and deliberately rounded.
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Where to start
You see which use case suits your industry as a starting point.
We treat your information confidentially and never sell it on.
A first estimate in five minutes
For a more precise calculation
The full check
15 questions go into more detail. The analysis includes a recommendation on where to start and shows typical pitfalls for your role.
We treat your information confidentially and never sell it on.
Transparency
How we calculate the potential
The AI Operations Self-Check is an estimate and not an audit. We disclose where our assumptions come from, how we process your answers and where the methodology reaches its limits.
Approach
Four steps from input to result
1
Understand the company (Block 1)
Industry, size, team, markets and sales channels determine the impact space: how large potential savings and pipeline effects can become at all.
2
Capture the status quo (Block 2)
Content production, sales process, reporting maturity and AI-tool usage show which starting points are still untapped. Those further along have smaller jumps, but more stable results.
3
Quantify the potential (Block 3)
Weekly effort for routine work, marketing spend and revenue potential provide the base values we apply industry multipliers to.
4
Derive orders of magnitude
We combine your answers with cautious industry factors (60 to 80% efficiency gain in content, 5 to 15% more pipeline in sales) and give ranges in euros. The values are deliberately rounded to avoid false precision.
Sources
Studies we rely on
BCG: The Widening AI Value Gap
60% of companies generate no material value despite continuous AI investments, only ~5% create value at scale. Main cause: missing operationalization, the “implementation gap” our approach directly answers.
bcg.com ↗ McKinsey: Global AI Survey 2025
88% of companies worldwide use AI in at least one business function. Adoption is no longer the bottleneck, the gap between adoption and impact is the core problem AI Operations solves.
mckinsey.com ↗ Gartner: 30% of GenAI projects abandoned after PoC by end of 2025
Three in ten GenAI pilots don't survive the proof of concept. Causes: poor data quality, unclear business cases, cost overruns. All factors our check asks about.
gartner.com ↗ MIT: State of AI in Business 2025
95% of all AI pilots never reach productive impact. Despite high adoption rates, almost all initiatives fail at integration, scaling and operationalization. That's the gap AI Operations closes as a discipline.
nanda.media.mit.edu ↗ BCG / McKinsey: Partner vs. In-house Implementation
The success rate is 67% with an external partner and 33% for in-house builds. With a partner, twice as many projects succeed. That is why we build AI Operations together with you.
bcg.com ↗ VDMA / PwC: AI in mechanical and plant engineering 2025
53% of mechanical engineers name marketing & sales as the most important GenAI use area. An industry-specific multiplier that feeds directly into our estimates, for mechanical engineering we raise the pipeline multiplier accordingly.
vdma.org ↗ McKinsey: The economic potential of generative AI
Quantifies the annual value-creation potential of GenAI at USD 2.6–4.4 trillion worldwide. Marketing & sales is among the four functions with the highest expected value contribution.
mckinsey.com ↗ DIHK: Digitalization Survey 2026
81% of companies cannot quantify their AI ROI, and over 75% see no measurable return yet. 53% distrust non-European providers. This is exactly the measurement gap the check addresses: a first, credible potential estimate.
dihk.de ↗ Stanford HAI: AI Index Report 2026
88% organizational adoption, but fewer than 10% have fully scaled AI in a single function. Inaccuracy is the most-cited AI risk at 74% (+14 points in one year), ahead of cybersecurity. Data quality and operations decide, not the model.
hai.stanford.edu ↗ ifo Institute: Business survey on AI usage
54.5% of German companies use AI (previous year: 40.9%), the classic mid-market trails at 47.2%, behind large enterprises (67.2%) and even small firms. The benchmark behind our company-size assessment.
ifo.de ↗ BCG: AI at Work 2026
47% of workers spend more time directing AI than doing their actual tasks. A clear AI strategy delivers +25 points of impact, better tools alone only +5. Strategy beats tooling 5:1. That's why the check examines structures, not tool lists.
bcg.com ↗ netzstrategen: Our own project experience
Industry multipliers for mechanical engineering, B2B mid-market, pharma and FMCG are based on our own measured values from productive engagements. Typical ranges: 50–75% reduction in agency costs, 35–60% effort reduction in reporting, 8–15% pipeline uplift through automated lead qualification.
Limits
What this check delivers and what it doesn't
The values shown are estimates based on typical industry benchmarks. They replace neither an audit, nor ROI modeling, nor due diligence.
We deliberately round in steps of €5,000 or €10,000 to avoid false precision. How much actually materialises depends on data quality, organisational maturity and discipline in implementation. We clarify this in the personal introductory call.
Important: A high potential does not mean the value will materialise by itself. It means that the starting point is there. How much of it you realise depends on the implementation. That is why we build together with your team. “From strategy to impact.”
First: your focus
What matters most to you?
Your choice decides where the result puts its emphasis. You can change it at any time.
Overview of all roles You first see what is possible overall. The result stays neutral.
Profit and margin: management Shows where AI affects profit and margin, with comparison values from mid-sized companies.
Marketing: head of marketing Shows where agency costs fall and what marketing contributes to the pipeline.
Sales: head of sales Shows how win rate, speed and forecasts in sales can improve.
Block 1: Your company
Which industry is your company in?
Different AI Operations approaches suit different industries.
Mechanical & Industrial Engineering Manufacturers, plant engineering, engineering services
Automotive Vehicle manufacturers, suppliers, mobility providers
B2B Services & IT Consulting, software, professional services
Finance & Insurance Banks, asset management, insurance
Media Publishers, broadcasting, digital media, content
Other industry Pharma, consumer goods, logistics, energy, other
Block 1: Your company
How many employees does your company have?
Size determines how strongly automation affects the business overall.
50 – 200 employees Lean structures, small teams
200 – 500 employees Growing company, clear departments
500 – 2,000 employees Larger mid-market
Over 2,000 employees Large enterprise or corporate group
Block 1: Your company
Which topics are particularly urgent for you right now?
✦ Multiple answers possible
Cut costs Reduce external spend, become more efficient
Accelerate growth More leads, better conversion, scale faster
Improve quality & consistency Better results, fewer errors, sharpen the brand
Relieve the team Take routine tasks off their plate, win back strategic time
Block 1: Your company
How large is your combined marketing and sales team?
Everyone in a marketing, sales or customer-success role, internal and external (field sales, agency, SDRs) combined. In mechanical engineering, sales engineers count, but technical engineering does not.
No dedicated team Marketing and sales happen on the side, via management, assistants or individuals
1 – 5 people Small team where everyone does a bit of everything and works closely together
5 – 15 people Structured team with clear roles and first specializations
More than 15 people Larger department with sub-teams, decentralized structures or multiple countries
Block 1: Your company
In how many countries and languages are you active?
Every additional language brings translation work, and that work is well suited to automation.
1 country, 1 language Operating nationally only
2 – 3 countries, 2 – 3 languages DACH region or adjacent markets
4 – 8 countries, 3 – 5 languages Active across Europe
More than 8 countries or 5+ languages Globally positioned
Block 1: Your company
Do you have e-commerce or digital sales channels?
Digital sales channels make far more automation possible, from product copy and lead nurturing to draft quotes.
No: no digital sales channel Sales run exclusively via personal contacts and field sales
First steps: inquiries via website or email forms No shop, but digital first contacts and inquiry processes exist
Yes: B2B shop or configuration portal Customers can configure, request or order products directly
Yes: active B2C or D2C e-commerce Online revenue is a relevant share of the total business
Block 2: Status quo
In which areas would you like to build AI into your processes?
✦ Multiple selection possible: pick all that apply
This tells us which use cases come first and where the effort pays off fastest.
Marketing collateral Documents and presentations for marketing and sales: proposals, product slides, factsheets, brochures
Content Content for emails, press releases, news, LinkedIn posts and other channels
Website Topic, product and campaign landing pages, creation and maintenance
Sales Enriching leads with sales-relevant information for faster qualification
Service Intake and enrichment of customer inquiries for faster, optimized handling
Another area I have a different process in mind, which we can discuss in the introductory call
Block 2: Status quo
How is your content and communications production set up today?
No fixed structures Content is created spontaneously and ad hoc, no clear processes, ownership or fixed budget
Mostly agency-dependent, roughly €30,000 – €120,000/year External providers deliver copy, translations, design and campaigns
1 – 3 internal people doing everything A small team does it all, and quality and rhythm vary
Own team with external agency support Internal team in place, agencies fill capacity or skill gaps, €20,000 – €80,000/year external
Well set up, but many manual processes Structure exists, but copy-paste, manual translation and repetition
I don't know the details Not my domain, please use an industry average
Block 2: Status quo
How structured is your sales process today?
No process defined Inquiries are rare and handled individually, no CRM, no prioritization, no system
Manual, response times often over 24 hours Process exists, but follow-ups slip through, tracking is patchy
CRM in place, but barely used System there, adoption missing, little transparency on pipeline value
Professionally set up Structured process, CRM actively used, clear pipeline. Automation as the next step
Block 2: Status quo
What does your data and reporting look like today?
Hardly any reporting No clear KPIs, decisions run on gut feeling
Manual reporting, roughly 8 – 20 hours/month Excel, manual exports, time-consuming and error-prone
First dashboards, but data silos and gaps Partly automated, but systems don't talk to each other
Sound reporting, forecasts still missing We see what was, but not what's coming
Block 2: Status quo
Which AI tools does your team use today?
✦ Multiple selection possible
ChatGPT / Claude / Gemini Ad hoc, individual, no fixed process
Microsoft Copilot Integrated in the Office context
Image AI / design tools Midjourney, Firefly, DALL-E
First automations n8n, Make, Zapier or similar
No AI tools in use yet We're just getting started
Block 3: Your potential
How many hours per week does your team spend on recurring, manual tasks?
For example writing copy, creating reports, gathering data, answering enquiries, translating content or setting up campaigns.
15 hours per week
few (2)medium (40)a lot (80+)
Block 3: Your potential
What do you spend annually on paid advertising, SEO and marketing technology?
This means: paid ads (Google, LinkedIn, Meta), SEO tools, marketing automation, analytics, CRM licenses. Not included: content-creation costs or agency fees, those feed into the calculation separately.
Under €20,000/year Hardly any paid advertising, few tools
€20,000 – €60,000/year First ad budgets, some tools in use
€60,000 – €150,000/year Active paid strategy, multiple platforms and tools
Over €150,000/year Significant ad budget, extensive technology stack
I don't know, please estimate Not my domain, please use an industry average for our size
Block 3: Your potential
How large is the annual business volume initiated through acquisition & sales?
This means the total value of all business initiated (new-customer inquiries, existing-account expansion, account growth), not just what actually closes. Example: 200 inquiries/year × avg. €12,500 deal value ≈ €2.5M. In mechanical engineering, existing-account business and trade-fair contacts count too.
Under €1M
€1 – 5M
€5 – 20M
Over €20M
Block 3: Your potential
How would you rate your readiness to introduce AI Operations?
An honest assessment helps us recommend the right entry point.
We're just exploring, no budget, no decision We're looking into the topic before we invest
We're interested, budget not yet released The topic is on the agenda, but no concrete decision yet
We're ready, a decision could come soon Internal pressure exists, budget can be mobilized
We want to start, now or within the next 3 months Clear mandate, budget released or in approval
Block 4: Your result
Final step, then you will see your result
After “Show result”, the range in euros appears directly on this page. You can open and share the result later via a link. If you like, you can then arrange a free 30-minute introductory call.
AI Operations Self-Check: your result
Estimated total potential per year
— €
Sum of savings in costs, tools and time and additional pipeline value. The figure is a rounded order of magnitude and not a promise.
Confidence score — / 95
How the confidence score works
The score shows how complete your answers are and therefore how reliable the order of magnitude is:
- Answered questions: every answer raises the score; key multipliers such as industry, size, spend and pipeline count the most.
- Own values: values entered via the sliders (hourly rate, spend, pipeline) add extra points.
- “I don't know” answers: where industry averages step in, the score drops.
Maximum 95 points · 90+ = high confidence · 65–89 = good confidence · 40–64 = first indication · below 40 = preliminary estimate
How it adds up
Savings and additional revenue
We show savings from more efficient processes and additional pipeline value from better acquisition separately, so you can see where each effect comes from.
What's behind the numbers
Evidence from studies and where to start
Here you see which study findings matter for your case, which typical pitfalls could apply to you and where best to start. Further down, you can calculate with your own values.
Calculate with your numbers
Move the sliders and the figures above update straight away. Your own values active
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More on the topic
Digital Impact: podcast and newsletter
How we think about AI Operations in practice: weekly AI insights, monthly longreads and updates on webinars and events, straight from the netzstrategen team.
The calculated figures are estimates based on typical industry values and your answers. We work out concrete numbers together in the introductory call.
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