A friendly white robot sitting at the center, surrounded by floating digital windows displaying business tasks like data analytics, social media management, financial tracking, and logistics. The scene uses a bright, colorful palette to represent modern AI integration in small business operations.

AI for Business: What Every Business Owner Should Know

What Is AI for Business?

AI (artificial intelligence) for business means using computer programmes that can learn and make decisions to help companies work smarter. This includes chatbots that handle customer questions, tools that write marketing content, systems that sort sales leads, and virtual assistants that complete multi-step tasks on your behalf. AI can save time and cut costs, but it works best when businesses understand both what it can do and where it falls short – before spending any money on it.


Over the last few months, we’ve increasingly been getting queries about AI in business especially as concerns websites, online marketing, and content creation and management. Not a week goes by when we don’t have an AI-related conversation with at least one of our clients. So, hopefully this guide will go some way to explain AI and how it is already in use by businesses. In my research for this post I have leaned on AI to help gather statistics and examples of AI usage in business.
NB: This is written in March 2026; with how quickly AI is changing, I advise checking other sources for information too as they may be more current.



Why AI Matters for Your Business Right Now

Let’s be honest, “AI” has become one of those words that gets thrown around so much that it might be losing all meaning to you. You’ve probably heard it in sales pitches, seen it in the news, and had at least one person in a meeting suggest that AI could “transform everything.” And you’ve probably thought: yes, but what does that actually mean for my business?

That’s exactly the right question to be asking. Because the truth is, AI is not magic. It won’t help with new leads and increased sales overnight, and it’s not going to replace your best staff any time soon. But if you understand it well enough to make good decisions about it, it can make your business more efficient, help you serve your customers better and give you a meaningful edge over competitors who are still sitting on the fence.

The numbers paint a striking picture of just how fast all of this is moving. According to McKinsey’s State of AI 2025 report, 78% of organisations now use AI in at least one business function – up from just 55% two years ago. And one new company in the UK is adopting AI every 60 seconds, according to Amazon Web Services research.

Whether you run a boutique hotel, a professional services firm, or an online retail shop, the questions are the same: What is AI? What can it actually do for me? And what should I be careful about? This guide hopefully answers all of that in plain English – no technical background required.

“Just as electricity transformed almost everything 100 years ago, today I actually have a hard time thinking of an industry that I don’t think AI will transform in the next several years.”

โ€” Andrew Ng, Co-founder of Coursera, former Head of Google Brain & Baidu AI ย ยทย  Stanford Graduate School of Business
๐Ÿ’ก What You’ll Take Away
By the end of this guide, you’ll have a solid enough understanding of AI to make informed decisions, ask the right questions of any supplier or tech partner, and start meaningful conversations with your team โ€” without feeling like you’re guessing.

What AI Actually Is (In Plain English)

Artificial intelligence is the ability of a computer programme to do things that normally need human thinking – things like understanding a question someone has typed, spotting a pattern in data, making a decision, or writing a paragraph of text.

Here’s a simple way to picture it. Imagine you hired a very fast, very well-read assistant who had read millions of books, websites, and documents. They can answer questions, write content, summarise things, and carry out instructions – often in seconds. That’s roughly what modern AI tools do.

The AI tools that most businesses are exploring today are built on something called a Large Language Model, or LLM. These are AI systems that have been trained on an enormous amount of text – think of the entire internet, plus vast libraries of books and documents – and have learned to understand and produce human language as a result. Tools like ChatGPT, Google Gemini and Claude are all built on these models.

๐Ÿ” Worth Knowing
When people say “AI” in a business context today, they usually mean AI that works with language – reading it, writing it, or responding to it. This is different from older forms of AI like spam filters or product recommendation engines, which have actually been around for years. You’ve been using AI longer than you think.

You may also hear the term Machine Learning. This is simply the process by which an AI system improves over time by learning from examples, rather than being given a fixed set of rules. The more data it sees, the better it gets.

The single most important thing to understand about AI is this: it does not “think” the way a human does. It is extraordinarily good at finding patterns and producing useful output – but it has no genuine understanding, no real-world experience, and no common sense in the way a person does. Keeping that in mind will help you make much smarter decisions about where to use it.


The AI Tools Every Business Should Know About

Rather than running through every AI product on the market (because there are hundreds if not thousands), here are the core ideas you’ll encounter – explained in the way they actually matter to your business.

Chatbots

A chatbot is a computer programme that can hold a text conversation with a person. You’ve almost certainly seen them – that little pop-up in the corner of a website asking “Hi, how can I help you today?”

Older chatbots were fairly limited. They followed a fixed script, so if a customer asked something slightly different from what the chatbot expected, the whole thing fell apart. Newer AI-powered chatbots are a completely different story. They understand natural language (the way people actually speak and type), handle complex or unexpected questions and can take actions like checking an order, booking a table or accessing a client’s file.

The business case for them is growing fast. Research from Master of Code Global shows that chatbots are now one of the top three AI use cases in business, alongside process automation and data analytics – deployed by 71% of organisations that have implemented AI solutions. And there’s a strong customer appetite for it too: 82% of consumers say they’re interested in using AI-powered chat to reach customer service, ask questions and resolve issues.

Real-World Examples
A hotel or events venue can use a chatbot to handle booking enquiries, answer questions about availability, and collect guest information โ€” 24 hours a day, without tying up your admin team. A law firm or accountancy practice could use one to answer common client questions and triage enquiries before they reach a fee-earner. A retailer can use one to track orders, handle returns queries and suggest products – all without a human agent involved.
โš ๏ธ Watch Out For This
A badly set-up chatbot is worse than no chatbot at all. If customers feel trapped in a loop with a bot that doesn’t understand them, they’ll leave – and they’ll remember. Always make sure there’s an easy, obvious way to reach a real person when the bot gets loopy and can’t help.

AI-Driven Search

Search is changing in a way that every business with a website needs to understand. Traditionally, someone would type a question into Google and get a list of links. They’d then click through several pages, read around, and piece together the answer.

AI-driven search does something different. It reads the relevant content for you and gives a direct answer – often pulling from multiple sources and presenting a tidy summary. Google’s AI Overviews, Microsoft Copilot in Bing, and tools like Perplexity AI all work this way.

For your business, this matters because it changes how people find you. If your website content isn’t clear, well-written, and genuinely useful, AI search tools may skip right past it when giving answers to potential customers. Businesses that understand this shift early – and create content that answers real questions directly – are going to have a significant advantage. This area is still in its infancy and trying to set up KPIs to measure effectiveness is difficult at the moment.

Generative AI

This is the category of AI that creates new content – written text, images, video scripts, email campaigns, social posts, product descriptions, and more. Tools like ChatGPT, Claude, Jasper, and Canva’s AI features all fall into this bucket.

The speed of adoption here has been remarkable. According to McKinsey, regular use of generative AI in business jumped from 33% of organisations in 2023 to 71% by 2024. For marketing and communications teams, this can be a real time-saver. Instead of staring at a blank screen for an hour, you can give an AI a brief and have a working first draft in seconds. That draft will almost certainly need editing – but starting from something is almost always faster than starting from nothing.

Real-World Examples
A retail brand could use generative AI to draft product descriptions for a new range, create social media captions for a seasonal campaign, and write promotional emails – all from a short brief. A professional services firm could use it to create first drafts of thought leadership articles, client newsletters or website FAQs. A restaurant or events venue could use it to write compelling descriptions of menus, packages or event spaces.

AI Agents

An AI agent is a step beyond a simple chatbot or content tool. Whereas a regular AI tool responds to one instruction at a time, an AI agent can carry out a sequence of tasks on your behalf – making decisions along the way, using tools, and working through a process from start to finish.

Imagine asking an assistant to research competitor pricing, summarise the findings, write a short report, and send it to your sales manager. An AI agent could potentially do all of that from a single instruction – browsing the web, pulling information together, creating a document, and sending an email, all without you guiding each step.

Sam Altman, CEO of OpenAI (the company behind ChatGPT), has been clear about how significant he sees this development. Writing on his personal blog in January 2025, he stated:

“In 2025, we may see the first AI agents ‘join the workforce’ and materially change the output of companies.”

โ€” Sam Altman, CEO of OpenAI ย ยทย  Reflections, January 2025

This technology is still developing, but early versions are already being used to automate business workflows – things like processing expense claims, responding to enquiries, scheduling follow-up calls, and updating customer records automatically. According to the Deloitte State of AI 2026 report, 62% of organisations are already experimenting with AI agents.

Agentic AI

“Agentic AI” is a term you’ll hear more and more. It describes AI systems that operate with a high degree of independence – not just responding to one prompt, but planning and working through an entire project on their own.

Think about the difference between a new team member who needs hand-holding at every step, versus a trusted colleague you can hand a project to and know it’ll come back done. Agentic AI is aiming to be more like the latter. It’s powerful – but it also requires careful thought about what you’re letting it do unsupervised, and what guardrails you have in place.

Deloitte’s research shows just how rapidly this space is moving: agentic AI usage is set to rise sharply over the next two years, yet only 1 in 5 companies currently has a mature approach to governing autonomous AI agents. That gap – between adoption and oversight – is worth paying attention to.

๐Ÿ’ก A Simple Way to Remember the Difference
Chatbot โ†’ answers one question at a time.
AI Agent โ†’ carries out a series of steps toward a goal.
Agentic AI โ†’ plans and works through a whole project with minimal hand-holding. Each level is more powerful โ€” and needs more thought before you hand it the keys.

AI That’s Already in Your Existing Tools

Here’s something a lot of businesses miss: you may already have access to AI features without realising it. Microsoft 365 Copilot brings AI into Word, Excel, Outlook, and Teams. Google Workspace has AI built into Gmail, Docs, and Sheets. HubSpot, Salesforce, Mailchimp, Xero, Canva – the list of everyday business tools quietly adding AI features is growing rapidly.

Satya Nadella, CEO of Microsoft, has spoken openly about how AI tools have become part of his own daily workflow โ€” using them to prepare for meetings, manage projects, and stay on top of priorities. Speaking at the Fast Company Innovation Festival, he said:

“I think this is really the time not to swim with conventional wisdom. Be playing with the technology. Be introspective as to where you are in your ability to adopt new stuff and change processes โ€” because I think that’s going to be key.”

โ€” Satya Nadella, CEO of Microsoft ย ยทย  CNBC, September 2024

Before signing up for a new AI subscription, it’s worth spending twenty minutes checking what the tools you already pay for can now do. You might already have more than you think.


How AI Can Help Marketing, Sales & Operations

40%

Average productivity boost reported by employees using AI tools

Upwork Research Institute, 2024

83%

of sales teams using AI saw revenue growth in 2024, vs 66% without AI

Fullview AI Statistics, 2025

37%

Average reduction in marketing costs for businesses using AI

Fullview AI Statistics, 2025

Marketing

Marketing is one of the areas where AI is having the most immediate, practical impact for businesses of all sizes. Here’s where it can earn its keep:

  • Content creation: First drafts of blog posts, social media captions, ad copy, email newsletters, and product descriptions – fast.
  • SEO and content strategy: Finding the right topics and keywords based on what your potential customers are actually searching for right now.
  • Email personalisation: Sending different content to different customer segments based on their behaviour – automatically, at scale.
  • Image and visual creation: Tools like Canva’s AI features can produce professional-looking visuals quickly, even without a designer on the team.
  • Analytics and insights: Making sense of website and campaign data without needing a specialist to interpret it for you.

Marketing and sales is now the most common area in which businesses report using generative AI, according to McKinsey – and it’s also where companies most often report meaningful revenue increases as a result. Businesses using AI for marketing report an average 39% increase in revenue alongside those cost reductions, based on data compiled by Fullview.

Example: Hospitality & Events
An events venue could use AI to write tailored pitch decks for corporate clients, generate seasonal promotional emails for a mailing list of thousands, and create engaging social content for each upcoming event – all without hiring additional marketing resource.

Sales

Sales teams are using AI to focus their energy on the conversations most likely to convert – and spend less time on admin.

  • Lead scoring: AI can look at your sales data and predict which enquiries are most likely to turn into business – so your team knows where to focus first.
  • Personalised outreach: Tailored follow-up emails can be drafted at scale, saving hours of manual writing without losing the personal touch.
  • Call and meeting summaries: Tools like Otter.ai or Microsoft Copilot can transcribe and summarise sales calls automatically, so nothing important gets missed.
  • CRM data entry: Automatically logging notes and updates after calls, so your team spends less time on admin and more time talking to clients.

The impact on deal velocity is particularly notable. Research shows that sales professionals who use AI weekly experience 78% shorter deal cycles on average – meaning less time from first contact to closed sale, for the same (or better) conversion rates.

Example: Professional Services
A consultancy or law firm can use AI to automatically summarise client meetings, draft follow-up emails, and flag which prospects haven’t been contacted recently – keeping the pipeline moving without anyone manually tracking it.

Operations and Day-to-Day Admin

Some of the most valuable applications of AI are the unglamorous, behind-the-scenes ones that quietly save hours every week.

  • Document processing: Reading invoices, purchase orders, or application forms and pulling out the key information automatically.
  • HR and recruitment: Screening CVs against a job spec, drafting job descriptions, or answering common employee questions through an internal chatbot.
  • Customer support: Handling routine questions at scale โ€” delivery times, return policies, booking details – so your team can focus on the tricky ones.
  • Scheduling: AI scheduling tools can find mutually available meeting times, send reminders, and manage diaries without any back-and-forth emails.

AI is already reducing customer service costs by an average of 30% in organisations that have deployed it properly, according to research cited by Fullview. For small businesses, where every hour counts, that kind of operational saving can be genuinely transformative.

Example: Retail & E-commerce
An online retailer could use AI to handle the bulk of customer service enquiries (order tracking, returns, stock questions), automatically generate product descriptions for new lines, and analyse which products are being searched for but not found – feeding directly into buying decisions.

The Pros & Cons of AI for Business

It would be easy to write a guide that only focuses on the exciting possibilities. But that wouldn’t actually help you. Here’s an honest look at both sides – because going in with realistic expectations is what makes the difference between a successful AI project and an expensive disappointment.

โœ… Where AI Genuinely Shines

  • Saves significant time on repetitive, predictable tasks
  • Works around the clock without breaks or sick days
  • Processes large amounts of information very quickly
  • Produces consistent output at scale
  • Can reduce costs meaningfully in the right areas
  • Makes professional content production more accessible
  • Helps smaller teams compete with bigger ones
  • Keeps improving as the technology develops

โš ๏ธ Where AI Falls Short

  • Doesn’t know your business deeply without being taught
  • Can “hallucinate” – confidently making things up
  • Lacks genuine creativity, judgement, and empathy
  • Struggles with situations it hasn’t been prepared for
  • Carries real data privacy risks if used carelessly
  • Always needs a human to review the output
  • Costs can add up quickly at scale
  • Brand voice needs careful attention to get right

 

Here’s a number worth sitting with: according to McKinsey’s 2025 research, over 80% of organisations using generative AI are not yet seeing a measurable impact on their overall bottom line. That doesn’t mean AI isn’t valuable – it means that using AI tools casually, without clear goals or proper integration into your processes, rarely delivers the results you’d hope for. The businesses seeing genuine returns are the ones treating AI strategically, not as an experiment to dabble with.

“Even with its very limited current capability and its very deep flaws, people are finding ways to use this tool for great productivity gains. AI has been somewhat demystified because people really use it now. And that’s always the best way to pull the world forward with a new technology.”

โ€” Sam Altman, CEO of OpenAI, speaking at Davos ย ยทย  World Economic Forum, January 2024
โš ๏ธ The Hallucination Problem โ€” Take This Seriously
“Hallucination” is the term used when an AI confidently states something completely false. It doesn’t know it’s wrong – it just produces the most plausible-sounding answer. A 2024 survey found that 47% of enterprise AI users admitted to making at least one major business decision based on hallucinated content. If you use AI to generate content with statistics, legal information, or specific facts, always verify independently before publishing.

The businesses that get the most value from AI are the ones that treat it as a capable assistant, not an autonomous expert. It works best when there’s always a human in the loop – reviewing the output, catching mistakes, and adding the judgement, warmth, and personality that only a person can bring. The Deloitte State of AI report backs this up: 76% of enterprises now include human review processes specifically to catch AI errors before they cause problems.


Common Mistakes Businesses Make With AI

Knowing what to avoid is just as important as knowing what to do. These are the most common pitfalls – and they’re easier to sidestep once you know to look out for them.

Mistake 1: Treating AI as a silver bullet

Start with a specific problem, not a general excitement about AI. Ask yourself: “What task takes my team the most time that doesn’t really need deep expertise?” That’s almost always the best place to start – and it gives you something concrete to measure. McKinsey’s research consistently shows that companies who define clear business goals for their AI projects outperform those who don’t.

Mistake 2: Publishing AI content without checking it

Always have a human review AI-generated content before it goes anywhere near a customer. Check facts, refine the tone, and make sure it sounds like your brand rather than a generic algorithm. Only 27% of organisations currently review all AI-generated content before use, according to McKinsey – which means a lot of businesses are taking a risk they may not even realise they’re taking.

Mistake 3: Putting sensitive data into public AI tools

Free or consumer-grade AI tools (like the basic version of ChatGPT) may use your inputs to improve their systems. Never paste in customer data, financial information, or confidential HR records. Use enterprise or privacy-focused versions where your data is protected. If you’re unsure, ask before you type.

Mistake 4: Choosing the tool before defining the problem

Don’t sign up for an AI tool just because someone was persuasive in a demo. Define the outcome you want first – then look for tools that solve that specific thing. “We want to reduce the time our team spends answering routine customer emails” is a great starting point. “We want to use AI” is not.

Mistake 5: Underestimating the learning curve

AI tools need to be set up well, given context about your business, and learned by your team. The Deloitte AI report identifies the skills gap as the single biggest barrier to AI integration – and education as the top way organisations are responding. Factor in time for training, and the results will be dramatically better.

Mistake 6: Ignoring your team’s concerns

Many employees worry – understandably – that AI might threaten their role. Be open and honest about why you’re introducing it and what it’s designed to do. Teams that feel involved and reassured are far more likely to use the tools effectively, and far less likely to quietly ignore them. Andrew Ng, one of the world’s leading AI experts, has noted that AI creates new demand for skills even as it automates certain tasks – the picture is rarely as simple as “AI takes jobs.”

Frequently Asked Questions

Do I need a big budget to start using AI in my business?

Not at all. Many AI tools have free tiers or are already included in software you’re already paying for – Microsoft 365, Google Workspace, HubSpot, and Canva all have AI features built in. Paid standalone tools typically start from around ยฃ15 to ยฃ30 per user per month, which is relatively modest compared to the time they can save. Research from the Upwork Research Institute found that frequent AI users save over nine hours of work per week on average – so even a modest subscription can pay for itself very quickly.

Will AI replace my staff?

For most businesses, AI will change what jobs involve rather than eliminate them altogether. The tasks most at risk are repetitive and predictable ones. Roles that involve building relationships, exercising judgement, thinking strategically, or handling complex and sensitive situations are much harder to automate. The World Economic Forum estimates that while AI may displace some roles, it will also create new ones – with a net gain projected globally by 2030. The people most likely to feel the impact are those who choose not to learn how to work alongside these tools.

Is my customer data safe if I use AI tools?

It depends entirely on the tool and how it’s been configured. Enterprise versions of most AI platforms come with strong data protection commitments and won’t use your inputs to train their models. Free or consumer versions may not offer the same guarantees. Always read the data processing terms before using any AI tool with business or customer information โ€” and if in doubt, ask a digital specialist to check for you.

What’s the difference between ChatGPT and other AI tools?

ChatGPT is a product made by a company called OpenAI. It’s the most well-known AI assistant, but it’s one of many. Claude (by Anthropic), Gemini (by Google), and Copilot (by Microsoft) all do similar things with different strengths, pricing, and integration options. Think of them like different brands of car – they’ll all get you there, but some are better suited to certain journeys than others.

How do I know if an AI tool is actually worth the money?

Put a number on the problem before you commit. How many hours per week does your team spend on the task in question? What’s the approximate hourly cost of that time? If an AI tool saves five hours a week at ยฃ25 per hour, that’s over ยฃ6,000 a year in recovered time – which makes most monthly subscriptions look very reasonable. Run that calculation for the specific problem you’re solving, and the answer usually becomes clear. A Mercer study found that 54% of business leaders believe their companies will not remain competitive beyond 2030 without adopting AI at scale – which adds another dimension to the cost of waiting.

Can AI help with my website?

Yes – in quite a few ways. AI can help write or improve your website content, support your SEO/GEO strategy, power a chatbot for customer enquiries, analyse visitor behaviour, and personalise the experience for different types of visitor. That said, building and maintaining a website that genuinely reflects your brand and performs well still requires human expertise. AI is a tool that supports good web strategy – it’s not a replacement for it. See our post on a popular AI-driven web design tool.

How is AI changing SEO and online search for businesses?

This is one of the most important shifts happening right now for any business with a website. AI-powered search tools (like Google’s AI Overviews) are starting to give users direct answers rather than lists of links. That means content that directly and clearly answers real questions is becoming more valuable than ever. If your website content is vague, generic, or thin, it’s at risk of being passed over entirely by AI-driven search. Getting your content strategy right – sooner rather than later – really does matter.

Your Next Steps: From Curious to Confident

Reading about AI is one thing. Actually doing something about it is another. Here’s a practical, step-by-step way to move forward without feeling overwhelmed.

๐Ÿ” Step 1: Find Your Biggest Time Drains

Ask your team what tasks take the most time but need the least expertise. Those are your best candidates for AI support – and the easiest wins to start with.

๐Ÿงช Step 2: Experiment Safely First

Try a free tool – ChatGPT, Claude, or Copilot – for one internal, low-stake task. Internal summaries or draft documents are ideal. Let your team get used to it before rolling it out to customers.

๐Ÿ“ Step 3: Set Some Simple Rules

Before going wider, agree on basic guidelines. When can AI be used? What always needs a human check? What data must never go into a public AI tool? A one-page policy is enough to start.

๐ŸŽ“ Step 4: Invest in Learning to Prompt

Writing good instructions for AI (“prompting”) is a genuine skill. The better the brief you give, the better the result you get. A small investment in learning this pays back quickly.

๐Ÿค Step 5: Get Expert Support

For anything more complex – AI on your website, automating sales workflows, or building a content strategy – work with a digital partner who genuinely knows this space and can guide you through it.

๐Ÿ“Š Step 6: Track What Changes

Measure time saved, errors reduced, or response times improved. This tells you what’s working, what isn’t, and where it makes sense to go deeper. Data beats enthusiasm every time.


Glossary: Words Worth Knowing

Here’s a quick reference for the terms you’re most likely to encounter when AI comes up in conversation – whether that’s with a supplier, a tech team, or a business contact who’s just read something on LinkedIn.

Artificial Intelligence (AI)

Computer programmes that can perform tasks normally requiring human thinking – such as understanding language, making decisions, or creating content.

Large Language Model (LLM)

The technology behind tools like ChatGPT and Claude. Trained on vast amounts of text, it can understand and produce human language in a very convincing way.

Prompt

The instruction or question you give to an AI tool. Better prompts – with more context and clarity – produce better results. This is a skill worth developing.

Hallucination

When an AI confidently states something that is completely wrong or made up. It doesn’t know it’s wrong – which is why human review is always essential.

Generative AI

AI that creates new content – text, images, audio, or video – rather than simply analysing or sorting existing information.

AI Agent

An AI system that can carry out a sequence of tasks, making decisions at each step – rather than just responding to one question at a time.

Agentic AI

A more advanced type of AI agent that can work through complex, multi-step projects with minimal guidance – planning its own approach to reach a goal.

Machine Learning

The way AI systems improve over time – by learning from examples and data, rather than following fixed rules someone programmed in advance.

Automation

Using technology to carry out tasks that would otherwise be done manually – like sending emails, updating records, or sorting information.

AI-Driven Search

Search engines that use AI to give users a direct answer rather than a list of links – changing how businesses need to think about their web content.

CRM

Customer Relationship Management software – tools like HubSpot or Salesforce that help businesses track and manage relationships with clients and prospects. Most now have AI features built in.

SEO

Search Engine Optimisation – the practice of making your website appear higher in search results. AI is changing how SEO works, which matters for any business with an online presence.

So, Where Does This Leave You?

AI is not a fad. It’s not going away, and it’s going to play an increasingly important role in how businesses operate over the coming years. The good news is that you don’t need to become a technology expert to take advantage of it. You just need to understand it well enough to make smart, informed decisions – and to ask the right questions before spending any time or money.

Start small. Pick a real problem. Experiment in a low-risk way. Check everything the AI produces before it reaches a customer. Build your team’s confidence gradually. And when you’re ready to go further – whether that’s an AI-powered chatbot on your website, smarter marketing automation, or a clearer content strategy for the age of AI search – make sure you’ve got the right support around you.

At UZURI Digital, we help businesses make sense of digital technology so they can invest wisely, avoid costly mistakes, and build something that genuinely works for them. If any of this has sparked questions you’d like to talk through, we’d love to hear from you.

Picture of Chandesh Parekh

Chandesh Parekh

A website accessibility / inclusivity consultant, general web & WordPress developer and reputation marketer, Chandesh has been professionally immersed in the world wide web for 25+ years. Chandesh on LinkedIn (opens in new tab)