We help organisations move beyond experiments to AI and automation that save time, reduce costs and sharpen decisions, built securely, governed properly and measured against real outcomes.
- Strategy to production
- Security-first by design
- Measured against business outcomes
88%
of organisations now use AI in at least one business function (McKinsey, 2025)
The basics
What is AI and automation?
The two terms are often used together, but they do different jobs. The real value comes when they're combined.
Automation is the older of the two. It uses software to carry out a defined sequence of steps, following rules someone has written down: when an order arrives, check stock, raise an invoice and notify the warehouse. Tools such as workflow platforms and robotic process automation (RPA) are excellent at this kind of high-volume, repeatable work, because they never tire and never skip a step. Their limit is that they can only follow the rules they're given, so they struggle with anything unstructured, such as a free-text email, a scanned contract or a request that doesn't fit the usual pattern.
Artificial intelligence fills that gap. Rather than following fixed rules, AI models learn patterns from large amounts of data, which lets them read and write natural language, classify documents, spot anomalies, make predictions and, with generative AI, create new text, code and images. Combined, the two become intelligent automation: AI interprets the messy, human side of a process and decides what should happen, automation reliably carries it out across your systems, and people review the decisions that carry real risk. For a business, that means processes that are faster, cheaper and more consistent, without losing the judgement and accountability that customers and regulators expect.
- A
Automation
Software that carries out repetitive, rule-based tasks the same way every time, like moving data between systems, routing requests or generating reports.
Example: Invoices are captured and entered into finance systems automatically.
- +
Artificial intelligence
Systems that learn from data to recognise patterns, understand language, make predictions and generate content, handling work that isn't fully predictable.
Example: An assistant reads customer emails and drafts accurate replies.
- =
Intelligent automation
AI and automation together: AI makes the judgement, automation carries out the steps, and people stay in control of the decisions that matter.
Example: Claims are read, checked, scored for risk and routed, end to end.
How far it's come
From simple rules to AI that reasons
AI isn't new, but the last few years have changed what it can do and how easily businesses can use it.
1990sā2000s
Rules and scripts
Macros, workflows and rule-based systems automate fixed, predictable tasks.
2010s
Machine learning
Models learn from data to forecast demand, detect fraud and personalise recommendations.
Mid-2010s
Deep learning
Computers learn to see, listen and translate, powering vision, speech and language tools.
2022 onwards
Generative AI
Large language models write, summarise, code and converse, putting AI in every employee's hands.
Now
AI agents
AI that plans and completes multi-step tasks across systems, with people supervising the outcome.
Business adoption of AI has more than quadrupled since 2017
McKinsey's annual global survey shows adoption climbing from one in five organisations in 2017 to almost nine in ten today, with the sharpest rise coming after generative AI arrived.
Source: McKinsey & Company, The state of AI global surveys, 2017ā2025
| Year | Share |
|---|---|
| 2017 | 20% |
| 2018 | 47% |
| 2019 | 58% |
| 2020 | 50% |
| 2021 | 56% |
| 2022 | 50% |
| 2023 | 55% |
| 2024 | 78% |
| 2025 | 88% |
AI in practice
Where AI is already making a difference
AI is most valuable when it's pointed at real, everyday work. These are some of the areas where we see the quickest returns.
Customer service
Assistants that answer common questions, summarise cases and draft replies for agents to approve.
Finance
Automated invoice processing, reconciliations, anomaly detection and faster month-end reporting.
Sales & marketing
Lead scoring, personalised outreach, content drafting and insight from customer data.
Operations
Demand forecasting, scheduling, document processing and quality checks.
People & HR
Faster onboarding, policy assistants and help with routine employee requests.
IT & security
Smarter ticket triage, code assistance and threat detection that spots what people would miss.
Popular AI models, tools and platforms
- OpenAI
- Claude
- Google Gemini
- Microsoft Copilot
- GitHub Copilot
- Mistral AI
- Meta
- Perplexity
- DeepSeek
- Hugging Face
- LangChain
- PyTorch
- TensorFlow
- Databricks
- Snowflake
- NVIDIA
- Zapier
- Make
- n8n
- UiPath
- Notion
- HubSpot
- Zendesk
- ElevenLabs
Technologies and apps
The AI tools businesses are integrating
There's no single AI product. Most organisations combine a few building blocks. We're independent: we help you choose what fits your systems, data and budget.
01
AI assistants and models
General-purpose models and copilots for writing, analysis and everyday work.
- OpenAI
- Claude
- Google Gemini
- Microsoft Copilot
- Mistral AI
- Meta
- Perplexity
- GitHub Copilot
02
Workflow automation
Connect systems and automate processes, from simple triggers to complex workflows.
- Power Automate
- Zapier
- Make
- n8n
- UiPath
03
Data and ML platforms
Where data is prepared, models are trained and AI is run at scale.
- Databricks
- Snowflake
- Google Cloud
- AWS
- Microsoft Azure
- NVIDIA
04
Build and integrate
Frameworks and libraries for building custom AI into your own products.
- LangChain
- Hugging Face
- PyTorch
- TensorFlow
- Python
- Ollama
Product names and logos are trademarks of their respective owners and are shown to illustrate the technologies available. Their use does not imply endorsement or partnership.
The benefits
What AI brings to an organisation
Productivity
Hours back from repetitive work, so people focus on what needs their judgement.
Lower costs
Fewer manual steps, fewer errors and less rework across core processes.
Better decisions
Insight from data that was too large or messy to use before.
Customer experience
Faster, more consistent and more personal service around the clock.
Scalability
Grow volume without growing headcount at the same rate.
Risk and compliance
Consistent checks, clear audit trails and earlier warning of problems.
Generative AI went mainstream in under two years
Source: McKinsey & Company, The state of AI, 2023ā2025
| Year | Share |
|---|---|
| 2023 | 33% |
| Early 2024 | 65% |
| Late 2024 | 71% |
The business perspective
What leaders are weighing up
For most organisations the question is no longer whether to use AI, but how to do it well. These are the questions we help leadership teams answer.
- Return on investment
- Which use cases will pay back, how quickly, and how will we measure it?
- Risk and governance
- How do we protect data, meet regulations and keep people accountable for decisions?
- People and skills
- How do we bring teams with us, and which roles will change?
- Build or buy
- When is an off-the-shelf tool enough, and when do we need something custom?
Getting started
How you can adopt AI to accelerate your business
- 1
Start with a business problem
Choose work that is frequent, measurable and frustrating, not the flashiest idea.
- 2
Get your data ready
AI is only as good as the data it can safely reach. Tidy, connect and secure it first.
- 3
Pilot small, measure honestly
Prove value with real users and clear success measures before scaling.
- 4
Put guardrails in place
Policies, access controls and human review, set up from the start.
- 5
Scale what works
Roll out, train teams and keep monitoring quality, cost and impact.
Our approach
The Anthrasec AI strategy, tailored to you
Every organisation's AI journey is different, so we don't sell a package. Our approach adapts to your goals, data and appetite for risk.
- 01
Discover
Workshops with your teams to map processes, data and pain points, and find the opportunities worth pursuing.
You get: A prioritised list of use cases with expected value
- 02
Design
Choose the right tools and architecture, and design security, privacy and human oversight in from the start.
You get: A solution design and delivery roadmap
- 03
Deliver
Build in short, tested increments with your people involved, proving value on real work before scaling.
You get: Working AI in production, measured against agreed goals
- 04
Enable
Train your teams, hand over clear documentation and set up the governance to use AI with confidence.
You get: Teams ready to use and own what we've built
- 05
Evolve
Monitor quality, cost and impact, then improve and extend as the technology and your business change.
You get: A continuously improving AI capability
Why Anthrasec
Why choose Anthrasec for AI
Security-first
We come from cybersecurity, so your data, access and compliance are protected from day one.
Independent advice
We recommend the tools that fit your business, not the ones we're paid to sell.
End-to-end delivery
Strategy, data, cloud, integration and support from one team, with no gaps between suppliers.
Outcomes, not demos
Every project starts with a measurable goal and reports against it.
Built on solid foundations
As an AWS Partner Network member, we build AI on well-architected, scalable cloud.
With you after launch
We monitor, maintain and improve what we deliver as your needs grow.
Common questions
AI and your business, answered
Do we need a lot of data to get started?
Not always. Many valuable uses of AI, like assistants, document processing and workflow automation, work with the information you already have. We'll assess what you have and tell you honestly what's possible.
Is our data safe if we use AI tools?
It can be, with the right choices. We help you select tools and settings that keep your data private, control who can access what, and meet your regulatory requirements.
Will AI replace our staff?
In our experience, AI works best taking on repetitive tasks so people can focus on judgement, relationships and higher-value work. We help you plan the change with your teams, not around them.
How long before we see results?
Focused pilots can show results within weeks. Larger programmes are delivered in stages, so value arrives early and builds over time.
Should we buy an off-the-shelf tool or build something custom?
Often a mix. Off-the-shelf tools are quick to adopt; custom solutions fit unique processes and data. We'll recommend the simplest option that meets your goals.
How do we measure whether AI is working?
We agree measures at the start, such as time saved, cost per transaction, accuracy or customer satisfaction, and report against them throughout.
Work with us
Ready to work with Anthrasec?
Let's schedule a meeting.
Pick a time that suits you and tell us a little about what you need. We'll come prepared, with the right people in the room.
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