Artificial Intelligence: From Future Promise to Business Reality

Its successful adoption is not just about selecting the most advanced algorithms. What truly determines success is how effectively a company understands, integrates, and governs its data.

At CRMT, we see this reality every day. The majority of advanced solutions we implement already embed artificial intelligence: not as a standalone add-on, but as a core element of business systems. When supported by high-quality data, AI delivers fast, tangible, and measurable impact.

What does AI actually enable in practice?

In recent years, generative AI has made headlines, often associated with tools like ChatGPT that assist with everyday tasks, from drafting emails to creating presentations. But in a business context, AI goes far beyond these general-purpose applications.

At CRMT, we see AI delivering measurable impact across four recurring use cases:

1. Document Processing and Information Extraction

Modern organisations generate and manage vast amounts of documentation – contracts, reports, forms, memos, and meeting notes. The challenge is that much of this information is unstructured, hiding key insights in free text.

AI transforms this process by automatically extracting amounts, dates, addresses, contacts, and document status, enriching content with metadata, and even preparing concise summaries.

Unlike a simple keyword search, AI understands context. It distinguishes relevant details and structures them so they can be directly applied in reporting, analytics, or archiving. What would take an employee hours of manual review, AI completes in minutes.

Impact: This approach delivers the most significant benefit in high-volume scenarios – from categorising incoming mail to summarising long-term contracts for strategic decision-making.

Intelligent Search Across Knowledge Bases

In many organisations, the problem is not a lack of information, but rather too much of it, as it is dispersed across departments, folders, and systems. Valuable knowledge exists, but it isn’t easy to access efficiently.

Here, advanced search is enhanced by retrieval-augmented generation (RAG), which comes into play. Employees can ask questions in natural language; AI understands the context, locates the most relevant internal content, and generates a clear, source-cited answer – whether it’s a policy, internal guideline, or meeting record.

Impact: This saves employees hours of unproductive searching, while improving trust by pointing directly to the source. Such solutions are already widely used as digital employee assistants, for enterprise-wide document search, and for instant access to policies, technical manuals, or project documentation.

3. Conversational Assistants and Internal Chatbots

Customer-facing chatbots are already prevalent, but similar technologies are also increasingly being deployed within companies to support employees.

Internal AI assistants help staff navigate procedures, find answers to FAQs, and even draft documents. By accessing relevant data sources, they deliver accurate, personalised responses.

Studies show that reliable internal assistants can reduce IT and HR support requests by up to 30%. Beyond cost savings, they provide consistent and rapid access to knowledge that was previously spread across multiple systems.

Example: An employee requests, “Prepare the monthly cost report by department.” AI retrieves the data, applies a predefined reporting model, and produces a draft document ready for review.

4. Workflow Automation

AI is not limited to interpreting information – it can also act on it. Increasingly, organisations leverage AI to automate repetitive tasks and support decision-making within workflows.

For example, AI can scan an incoming email, recognise an open task, suggest a reply, or trigger the following action, such as routing content to the right system or notifying the responsible team. In advanced environments, AI operates autonomously in processes like claim handling, document approval, or anomaly detection.

A transitional model (assisted automation) leaves the final decision to the user but improves efficiency, consistency, and responsiveness. This allows companies to adopt AI gradually without disrupting existing processes.

Data: The Critical Foundation for AI

Across all use cases, one factor stands out: data. AI is not a miracle solution – it is a powerful engine that only works with structured, connected, and trustworthy inputs. Without a solid data foundation, even the most advanced models cannot deliver reliable results.

This is where CRMT comes in. We help organisations:

• Build robust data environments
• Integrate and connect distributed data sources
• Ensure compliance and security
• Deploy AI-enabled solutions that directly support core functions such as corporate performance management (CPM), business intelligence (BI), controlling, and regulatory reporting.

Together with our partners, we design and implement architectures and technologies aligned with business priorities, ensuring that AI is not only implemented but also delivers measurable value from day one.

Beyond Technology: The Strategic Dimension of AI

Discussions about AI often revolve around models, infrastructure, and the latest trends. But the real business questions are different:

• What are we trying to achieve with AI?
• Which processes hold the highest potential for transformation?
• Do we have the right data, and can we trust it?

That is why AI adoption must be treated as a strategic initiative, not just a technical upgrade. At CRMT, we bridge the gap between business objectives, data readiness, and technology – ensuring AI becomes an integral, value-creating part of your operations.

Considering AI for your business?
Let’s start where it matters most – with your data. Contact us to explore how we can tailor the right solution to meet your needs.