AI for Business: 8 Ways to Cut Costs and Improve Efficiency
8 ways in which AI can save your business money
To me, a profitable business is the aim of any commercial enterprise. However, in the current economic climate, we’re a long way from finding money growing on trees. What we can do is work to reduce our overheads and streamline our work processes using AI and Machine Learning.
There’s currently a lot of talk and interest in how Machine Learning (which I prefer to use over the term AI) can replace humans entirely. Undoubtedly this is a very complex and impressive idea, but ask yourself this question… do you believe a piece of software can truly replace your best staff member? For me, it doesn’t, and never will, and is no more a replacement for a human than a calculator is a replacement for a mathematician or an accountant.
On the other hand, Machine Learning, which uses pattern matching algorithms efficiently handles repetitive task and tell you what a successful outcome looks like. With enough examples, it will ‘learn’ to execute that task faster than any person could. In this context, a pattern can be a customer query, a passport scan, a marketing email, or a supply chain change. The flip side is that if you give it a task requiring genuine empathy, the Machine Learning algorithm will try and match it against cold logic, often failing to read the situation.
The ability to recognise and automate these patterns makes for a very useful tool, allowing business to strip away the mundane administration that can costs you business thousands of pounds and time in man-hours.
Here are several ways this technology can keep your overheads down.
Automating Customer Support
Customer service is vital, but paying a team to answer the same question about opening hours at 3 am is a drain on resources. Machine Learning chatbots can learn your FAQs and website data to provide human-level answers to routine queries.
It doesn’t get tired. It doesn’t get grumpy if a customer is rude, it doesn’t need a holiday… it just processes tickets. By filtering out the 80% of routine questions, you allow your human staff to focus on the complex issues that actually require empathy and critical thinking. You aren’t replacing the team; you are supercharging their efficiency and augmenting them.
Creating Basic Software Applications Without a Developer
To me, bespoke software development is an art form, but not every problem requires a Michelangelo. There are now ‘No-Code’ and ‘Low-Code’ platforms driven by AI that allow business owners to build internal tools, such as a holiday booking system or a simple stock inventory tracker.
The AI interprets requests given to it in natural human language and builds the complex code structure for you. While it falls short of building a complex, enterprise-level secure platform (please don’t try to build a banking app this way), it can save you tens of thousands of pounds in development costs for simple, internal utilities.
Creating Blog Posts and Social Media Posts Without a Copywriter
Content is king, but copywriters can be expensive for day-to-day content writing. Generative AI tools can churn out blog post drafts, LinkedIn updates, and Tweets in seconds. Show it a topic, tell it the tone, and it will generate detailed readable text.
However, there is a drawback. As I mentioned, the AI doesn’t ‘understand’ what it writes. It predicts the next word based on probability. It can be bland and factually confident but incorrect. Use it to generate the first draft and then have a human rewrite it into something better. It saves hours of staring at a blank page, even if it doesn’t replace the final polished article.
Email to CRM Integration
Salespeople hate data entry. It is the bane of their existence. Machine Learning tools can now sit between your email server and your Customer Relationship Management (CRM) system. They ‘read’ the emails, identify new leads, pull out phone numbers and meeting dates, and automatically populate the CRM.
This removes the “I forgot to log that call” excuse and ensures your pipeline data is accurate without your highest earners wasting time on admin.
Automatic Extraction of Text from Uploaded Documents
If your business deals with onboarding, such as estate agents, recruitment or finance you likely have to handle passports and driving licences. Manually typing out passport numbers is prone to human error and incredibly slow.
Computer Vision (a subset of Machine Learning) can scan an image of a passport, recognise the layout, and extract the name, DOB, and passport number into your database instantly. It matches the pattern of the document, verifies it isn’t a blurry photo of a cat, and digitises the data. It’s faster, more accurate, and significantly cheaper than paying a human to type data all day.
Predictive Maintenance for Equipment
For our clients in manufacturing here in Lancashire and beyond, equipment failure is a massive cost. Usually, you wait for a machine to break, or you replace parts on a schedule whether they need it or not.
Machine Learning analyses the vibrations and heat patterns of your machinery. It learns the ‘sound’ of a healthy electric motor. When that pitch changes slightly, the system can be set to alert you that a bearing is about to fail. You fix it during a lunch break for £50, rather than halting production for two days when it seizes up.
Inventory and Demand Forecasting
Stock sitting on a shelf is dead money. Running out of stock is lost money. Humans are notoriously bad at predicting demand – we rely on instinct or last year’s sales spreadsheet.
AI algorithms can crunch vast datasets: weather patterns, local events, historical sales, and current trends. It might notice that every time it rains on a Tuesday in November, sales of a specific widget go up by 15%. It instructs you to order just enough stock to meet demand, reducing waste and storage costs.
Fraud Detection and Financial Anomalies
Finally, protecting the money you already have is just as important as making more. In financial transactions, Machine Learning is the ultimate watchdog. It learns your business’s typical spending and transaction patterns.
If an invoice comes in that looks slightly different (maybe the logo pixelation is off, or the bank account details have shifted) the system can flag it. It spots the patterns of a scam that a busy accounts assistant might miss. It’s the digital equivalent of a guard dog that never sleeps.
The Reality Check
However, there is a drawback. Machine Learning is particularly bad at explaining its decisions and cannot (usually) describe why it flagged a legitimate customer as fraud or why it wrote a blog post that sounds slightly robotic. This is the opposite of a human expert, who can explain the nuance of a decision.
Not only does this require a level of supervision, but it can result in a lack of trust from your team if deployed poorly. If you automate everything without strategy, you risk alienating your customers who just want to speak to a person.
For now, I’ll continue to advise our clients to use Machine Learning as a efficiency improvement tool rather than a replacement for human effort. But who knows… maybe one day, your accounting software might say, ‘Look, I can see you’re worried about the tax bill. I’ve moved some numbers around, take a stress pill’. Thankfully, we are a long way off The Matrix… for now… I believe!
Need help navigating the hype surrounding AI?
At our Lancashire Office, we specialise in separating the science fiction from the business facts. If you want to know which of these technologies can actually save you money today, without the jargon, we offer a free consultation to review your current processes. Let’s have a brew and chat about how we can get the machines working for you.