AI has gone from concept to daily reality faster than almost any technology before it. What started as a research topic is now embedded in the tools businesses use every day: from customer service and fraud detection to HR processes, financial forecasting, and legal operations. No industry has been left untouched, and no function within a business operates entirely outside its reach.
Understanding what artificial intelligence actually is — and what it can realistically do — matters for anyone making decisions about how their organization works. This article covers the core definition, how AI functions in practice, and where it is creating the most concrete value for business operations, including in legal and contract management.
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Artificial Intelligence (AI): Definition
Artificial intelligence is the set of skills, knowledge, and techniques aimed at developing computer programs that can simulate human intelligence.
In practice, this means that AI programs can analyze data the way a human would: by picking out key information from a text, comparing and contrasting data to draw conclusions, and adapting their analytical capacity as new data comes in. Machine learning is central to this — it gives AI systems flexibility, allowing them to improve over time based on new inputs rather than following fixed rules.
Some Background and Examples
The term “artificial intelligence” is not new. Alan Turing — the father of computer science — first described the concept in the 1950s. His definition: a machine demonstrates intelligence when a person cannot distinguish its response from a human one.
What has changed dramatically is the scale and accessibility of AI applications. The most familiar examples include:
- Generative AI (ChatGPT, Claude, Gemini): tools that draft text, answer questions, and summarize documents based on natural language prompts;
- Voice recognition: used by applications such as Siri (Apple) or Alexa (Amazon);
- Image recognition: accessible to anyone via tools like Google Lens;
- Optical character recognition (OCR): detects and reads text embedded in images or scanned documents.
The generative AI wave since 2022 has accelerated adoption across every industry. In the legal sector specifically, the shift from experimentation to active deployment happened in under two years. Faster than any previous legal technology cycle.
What Are the Different Types of Artificial Intelligence?
Not all AI works the same way. There are three broad categories worth knowing:
- Narrow AI is the most common form today. It is designed to do one specific task well: recognise a face, translate a sentence, flag a suspicious transaction. Every AI tool you use in daily business life is narrow AI.
- General AI refers to a system that could perform any intellectual task a human can. It does not exist yet. It remains a research goal, not a commercial reality.
- Generative AI is the most recent shift. Unlike earlier AI that only analysed or classified data, generative AI produces new content: text, images, code, summaries. It is the technology behind ChatGPT, Claude, and similar tools, and it is what has driven the acceleration in AI adoption since 2022.
For business purposes, the distinction that matters most is between general-purpose AI tools and purpose-built AI trained for a specific domain, such as legal or finance. The difference shows up in accuracy, reliability, and data security.
How Are Businesses Using Artificial Intelligence Today?
AI is running in production across every major business function. A few concrete examples:
- Finance: anomaly detection in transactions, automated reporting, audit preparation
- Human resources: application screening, attrition forecasting, onboarding personalisation
- Customer service: first-line query handling, intelligent routing, response drafting
- Sales and marketing: lead scoring, content personalisation, contract summarisation
- Legal and compliance: contract risk review, regulatory monitoring, entity management, board meeting preparation
The common thread across all of these: AI handles the high-volume, rules-based work so that the people responsible for decisions can focus on judgment, not administration.
Gartner projects that by 2028, legal technology budgets alone will double to support expanded AI and agentic capabilities. That is a signal of how seriously organisations are treating this shift across the business.
Benefits and Risks of Artificial Intelligence
The main benefits:
- Speed: AI processes large volumes of data in seconds. Tasks that take a human hours can be completed in minutes.
- Consistency: AI applies the same standard every time, without fatigue or oversight gaps.
- Cost reduction: automating repetitive tasks reduces the resources required to handle routine work.
- Better decisions: AI surfaces patterns and insights across datasets too large for manual review, giving decision-makers a fuller picture.
The main risks:
In regulated industries like legal and finance, data privacy is the most critical risk to manage. The question is not whether to use AI, but which AI tools meet the security and governance standards your organisation requires.
Artificial Intelligence and Legal Work: A Practical Combination
Contract management is one of the most complex operational challenges legal teams face. A contract is a living document with a long lifecycle: from drafting and negotiation to execution, amendment, and renewal. These documents pass through multiple hands — inside and outside the company — and any gap in oversight can expose the organization to legal and financial risk.
AI addresses most of the friction points in this process directly. The use cases that deliver measurable value include:
- Extracting key information from contracts — deadlines, important clauses, amounts — without manual reading;
- Identifying risk in non-standard or non-compliant clauses;
- Monitoring contract performance through statistical analyses and dashboards;
- Drafting standard agreements with the help of smart templates.
These capabilities save time and reduce risk simultaneously: missed renewals, non-compliance, and incorrect amounts are among the most common — and costly — contract management failures.
The same AI logic extends beyond contracts. Legal teams are applying it to entity management (tracking compliance obligations across subsidiaries), board governance (generating meeting minutes, summarizing board packs), and matter management (surfacing similar past cases, tracking external counsel costs). The underlying benefit is the same in each area: fewer manual steps, less risk of human error, and faster access to the information that matters.
➡️ Read also: AI in Legal Operations: Transform Your Legal Team
How DiliTrust Uses AI Across the Legal Function
DiliTrust has been developing AI specifically for legal and governance work since 2017. Lini, the AI engine powers every module of the platform: Contract Lifecycle Management, Entity Management, Matter Management, Board Portal, and Dataroom. One AI, one platform, one connected data layer.
Lini is built on DiliTrust’s own infrastructure. For teams that require a specific underlying model for compliance or data residency reasons, DiliTrust also offers a Bring-Your-Own-LLM option. The platform is certified to ISO 27001 and SOC 2 Type 2, and is designed to support alignment with the EU AI Act.
In practice, Lini handles the tasks that take the most time without requiring a lawyer’s judgment:
- Contract data extraction and risk detection: flags non-compliant clauses and deviations from your playbooks;
- Ask Lini: a full-page AI assistant that answers questions across one or multiple contracts, compares document versions, and searches real-time regulatory sources with cited references;
- Document summarization: one-click summaries across all document formats including scanned files;
- Board minutes generation: produces draft minutes from agenda and audio recordings in minutes;
- Legal entity queries: natural-language questions answered across your full entity and mandate data.
For legal teams managing high volumes across multiple jurisdictions, the time savings compound quickly. DiliTrust estimates that teams using Lini across the full suite save over 1.5 working weeks per month.
How AI saves legal teams 1.5 weeks every month
Manual contract review takes more time than it should. Watch this 30-minute webinar replay to see how AI handles the heavy lifting — from clause flagging to compliance checks — so your team focuses on what requires legal judgment.
AI is not a gimmick. When it is purpose-built for legal work and deployed on infrastructure that meets enterprise security standards, it addresses the real operational problems legal teams face and frees lawyers to focus on the work that actually requires their expertise.
Want to see AI in action across your legal workflows?
Our team can walk you through a live demo tailored to your use case.
Frequently Asked Questions About Artificial Intelligence
Artificial intelligence is the broad concept: machines that simulate human reasoning. Machine learning is a subset of AI. It is the specific technique by which systems improve their performance by learning from data, without being explicitly reprogrammed for every new scenario.
Generative AI refers to AI systems that can produce new content — text, images, code, audio — based on a prompt. Tools like ChatGPT, Claude, and Gemini are examples. They are trained on large datasets and generate outputs that mimic human-produced content.
AI replaces specific tasks, not entire roles. Roles focused on judgment, relationships, strategy, and creative problem-solving are the least exposed. Roles built primarily around repetitive, rules-based tasks are changing the most. Most organisations are seeing AI shift what jobs require, rather than eliminate them outright.
The most cited risks are data privacy, algorithmic bias, lack of transparency in how decisions are made, and over-reliance on outputs that have not been verified by a human. In regulated industries like legal and finance, the additional risk is using AI tools that do not meet the data governance standards required for privileged or sensitive information.
