Artificial intelligence is no longer a future promise for business — it’s a competitive advantage some companies are using today while others are still deciding whether the timing is right. The gap between the two grows every quarter.
The problem isn’t the technology. Today’s AI models are extraordinarily capable, and using them costs a fraction of what it used to: GPT-3.5-level performance was more than 280 times cheaper in October 2024 than in November 2022 (Stanford AI Index). The problem is knowing what to implement, in what order, and how to manage the process so it delivers real returns instead of becoming another technology project that never reaches production.
What can artificial intelligence do for your company?
Artificial intelligence can transform almost any business process that involves historical data, repetitive decisions, or high-volume, low-variability work. But not everything AI can do has the same return or the same implementation complexity.
The applications with the clearest return for midsize companies include demand forecasting that cuts capital tied up in inventory, anomaly detection that reduces costly quality defects in production, document management automation that frees up hours of skilled work every week, personalized sales communications that lift conversion rates, and predictive maintenance that reduces unplanned downtime on critical machinery.
All of these have measured results at companies comparable to yours. They aren’t experiments or lab use cases.
What AI adoption gives your company
- Automated high-volume, repetitive work: document classification, data extraction, answers to common questions, recurring reports. AI does in seconds what now takes skilled people hours.
- Forecasts that improve operational decisions: knowing in advance what will happen with demand, customers, or equipment lets you act proactively instead of reactively.
- Better quality without higher costs: computer vision systems detect defects with a precision and speed no human inspector can match, at a minimal cost per unit inspected.
- Personalization at scale: offering the right proposal to the right customer at the right time is no longer reserved for large companies with hundred-person data science teams.
- Data as a strategic asset: AI makes the data you already have far more valuable. You don’t need to collect more data — you need to get more out of what you have.
How we implement AI in companies
These phases apply the relevant stages of DALIA to this service.
Phase 1: Diagnosis. We start by understanding the business, not the technology. We identify the processes with the most potential and the specific obstacles holding them back. This diagnosis shapes everything else.
Phase 2: Design. We design the technically right solution for the problem — not the most sophisticated or the most fashionable. The right architecture is the simplest one that solves the problem with the data available.
Phase 3: Implementation. We work in short cycles with visible results from the first few weeks. We integrate with your existing systems without replacing them, and we verify that the system works under your real operating conditions.
Phase 4: Handoff and maintenance. We train your team to use the system with confidence and interpret its outputs correctly. We monitor performance in production and make adjustments as needed.
Which applications make the most sense in each industry
Each industry has traits that determine which AI applications make the most sense. Manufacturing — automotive, metals, food processing — runs processes with large volumes of operational data, ideal for predictive models. Services such as tourism, hospitality, and retail have customer data that enables high-return personalization. Professional services — clinics, law firms, accounting practices — carry document workloads that generative AI automates with a fast, clear return.
Frequently asked questions
How much does it cost to implement artificial intelligence in a company? The range is very wide, depending on scope. A well-defined first project can cost between €8,000 and €25,000. A broader transformation can exceed €100,000, though it’s almost always partly funded by savings from the early phases. The first step — the assessment call — is free.
Are there grants or subsidies for implementing AI? Yes. At EU level, the Digital Europe Programme funds a network of European Digital Innovation Hubs (EDIH) that help companies adopt AI, and Horizon Europe and the European Regional Development Fund (ERDF) fund innovation projects that can include it. Each member state and region also runs its own digitalization, training, and innovation programs. We help you identify which apply to you and prepare the paperwork.
Will AI eliminate jobs in my company? Experience from real projects shows that AI eliminates repetitive tasks, not jobs. When the transition is well managed, employees whose tasks are automated move on to higher-value work. Companies that plan it well gain productivity without losing talent.
Where do I start if I know nothing about AI? With a free 15-minute conversation. On that call, we identify the processes in your company with the most AI potential and explain what each would take and what return you could expect.
Start implementing AI in your company
The time to act is now. Every quarter without AI hands your most agile competitors another quarter’s head start. The initial assessment is free.
Email us at [email protected] or book your 15-minute assessment.