The right and wrong ways to implement AI into your business.

It’s becoming harder and harder to ignore AI in your business. If you use any sort of software, the likelihood is that it’s currently integrating some form of generative AI. Heck, even fridges and microwaves are injecting AI into their software, let alone your favourite software.

It’s a great time to be alive, and it’s incredibly exciting to see all the benefits we’re reaping from AI tools, but it can also be scary.

How do you keep up? How do you know which tool to use? How do you discuss the tools you’re using with your clients? How do you control what your employees are doing on AI?

There’s no easy answer. 

But I can practically guarantee that most of these questions are being asked by your peers, so do not feel like you’re the only one who’s confused.

Before getting into some specific advice, however, I just want to give one word of warning. Don’t assume this is just going to go away. This is not the Metaverse. This is not AR and VR. This is not 360-degree videos. Their time may still come, but they exploded onto the scene before the world was ready for them. AI is here today, and here to stay and its transformational effects on businesses are profound.

And while I don’t think that you’ll lose your job (or your clients) to AI just yet, I am pretty certain that you’re going to lose your job (or your clients) to a company that’s leveraging AI better than you are.

It’s like living through the industrial revolution and ignoring automation of manufacture. Sure, there’s still room for small-scale artisans, but the people with big machines are always going to outgun anyone manufacturing manually.

Right ways to implement AI tools

Overall, the first thing to look at when considering AI tools and technology is that these are tools to help you do your job better or more efficiently. You should look for areas of your business that could do with assistance in automation or in making sense of large swathes of data. In general, any task that’s heavily process driven and is repeated can probably be helped by some AI tool or another.

I’m not going to cover many examples of good ways to use AI because most of the tools that make your life easier are industry-specific, but if you go over the few examples I’ve chosen below, you can see the thought process.

Help with Research

Most of our work needs a deep understanding of the industry we’re working in with our clients. AI tools can be invaluable at quickly getting up to speed with industries, markets or areas of specialisation. This can be true for any industry, I can’t think of any industry in which a better understanding of your industry will not prove to be useful.

It’s also an excellent way to learn more about other roles within your company. Especially as a business leader, if you can learn to leverage AI tools well you can ask far better questions of your more technical reports.

Help with Decision Making

If you have large swathes of data or a large amount of information about a specific subject, AI is an excellent way to make sense of it all, to query it and to help collect all the background information you need to make a decision about something. Think about the benefit you could extract from dumping all your meeting notes about a subject, or all the historical data from something, into one large dataset and having the ability to query it in easy to understand, human commands.

Help with Automation of Repetitive Tasks

AI is excellent at helping with repetitive tasks. Think transcribing voice notes, for example. Or recognising text and handwriting in large volumes. These are tasks that an AI tool can do in minutes what a human can do in days or weeks. As long as you can describe the process well, then you can probably find someone to leverage existing AI tools to do the job for you. 

Help with Time Management

One of our favourite tools to use at Switch is Clockwise, a calendar tool that saves us hours of time every week to find time in our schedules. It also looks at your individual calendar and optimises it to give you more focus time. You can always override its suggestions manually, but the benefit of using it has been massive for us.

Help with Customer Service

If you have a good enough description of all the normal queries you usually get with customer support, then it’s relatively easy to teach an AI tool to answer your customer queries online. This won’t replace human interactions when needed, but AI can offer an amazing customer experience if it can solve most of your customer queries in seconds. Your customers can get a much better service if most of their queries are answered quickly.

Wrong ways to implement AI tools

There are many more ways to leverage AI tools than the ones I covered above, and I’d be happy to discuss them in more detail if you want to reach out to me at any point. But I’m even more concerned about people looking at AI tools and seeing them in the wrong light. Just like they can be extremely helpful, they can be extremely dangerous (or downright stupid).

To Save on HR Costs

This is more of a question of approach than of actual implementation. If you’re looking at AI tools as a way to cut down on your HR costs, then you’re probably looking at it from the wrong perspective. Yes, by looking at the massive layoffs that big tech companies are making, you might be inclined to think that AI is definitely going to help with savings, but that’s just missing the woods for the trees. Big tech companies are laying off people from non-AI areas because it’s a business decision to focus on AI tools, not because AI tools are replacing humans. In most cases, they had overhired for growth and are actually now just doubling down on AI solutions instead, clearing out people from other divisions.

AI tools still need humans to make sense of them, and if you think otherwise you’re going to be very disappointed.

To Take Decisions on Your Behalf

AI tools are excellent at helping you make sense of information to make better decisions, but they should not be relied on to make decisions themselves (at this point in time), especially with tools that are more generic in nature. AI tools can definitely make better decisions in specialised scenarios. But don’t use AI tools to make decisions on your behalf when screening CVs, or when figuring out who to hire or fire, for example. Don’t rely on generic AI tools to tell you where to invest or where to spend your money. Use them to gather and make sense of information, but you should be the ultimate decision-maker.

To Produce Content on Your Behalf

I’ve seen so much obviously AI-generated content that it’s scary. It’s even worse when the person generating the content has clearly not even bothered to learn how to prompt well or how to make sense of the content that’s being output. I recently received an email from a potential supplier who very obviously just asked ChatGPT to write an email to help sell me something. The email could be seen as a ChatGPT effort from miles away, and what made it even worse was that the context of the email made no sense, so if the person sending the email had even bothered for a minute or two to read the email they were sending out, they’d have smelt a rat before sending it.

Think about the content you’re putting out there on behalf of your brand. Think about what your audience thinks of you. If you’re going to rely on a tool to create your content, at the very least take the time to learn how to prompt well and how to edit your content to make it make sense, but by the time you do that you can probably have produced the content yourself.

And in the end…

There are hundreds of ways to use AI to try to get ahead of the game (or at the very least to not be left behind). Not all of them are good. Not all of them will offer you a real advantage. 

Think about the sustainability of your decisions, learn as much as you can about the tools there are out there, keep up to date and keep an open mind.

It might seem scary, especially because there’s so much happening at any given time, but trust me, it’s just as exciting as it is frightening. Once you start seeing the real benefits of finding tools to take the boring bits of your work away, you’ll be a convert.

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Get a designed PDF copy of Business Intelligence Trends 2024

If you don’t have the time to read this article now, you can download the PDF version of Business Intelligence Trends 2024 for free by clicking below. Otherwise, just keep reading.

Wait, why are we talking about Business Intelligence tech?

If you’ve been following our trend reports for the last few years, you’ll notice that we’ve never broached the subject of Business Intelligence. 

Because we’re not a tech or software company. 

Our speciality is the translation of technical expertise and experience into clear communication. So far, our trend reports have translated our own knowledge and foresight, but we understand that businesses need more than just guidance on brand and communication to excel. 

To extend the usefulness of these trend documents, we’ve collaborated with our tech partners at Cleverbit Software to deliver this report on a tool that can be the difference between surviving and flourishing for businesses of all sizes: BI. If you’re new to the field, we recommend taking a look at Cleverbit’s own content on the subject. They literally wrote the book on Business Intelligence.

But if you’re aware of the essentials, and are looking at what the next year has in store, keep reading.

Business Intelligence in 2024: Data Quality, Governance, and AI-Driven Trends

As we journey through 2024, the landscape of Business Intelligence (BI) is undergoing a transformation that is both profound and multi-dimensional. This transformation is not just about the adoption of advanced technologies; it’s an evolution in the very ethos of how businesses interact with data.

Businesses who have already invested in business intelligence software will have an edge above their other competitors, having been grandfathered into the functions of business intelligence before this point, however despite the significant expansion within the BI industry, 2024 makes it far more accessible to companies who haven’t yet taken the plunge – and a far greater need. Significantly more than in previous years, business intelligence software is no longer something that can be put aside because of the expense: the staggering quantity of data that is heading to business in 2024 is impossible to parse using humans. 

Main BI Predictions for 2024

1. Explainable AI to reinvigorate the way businesses consume and manage data. 
2. Natural language processing will increase the amount of data sets available. 
3. Collaborative BI technologies will be on the rise, leading to a greater proportion of cloud-based BI systems. 
4. Renewed importance for data quality and data governance.
5. The unavoidable implementation of democratic data.

Trend 1: AI will reinvigorate the way businesses consume and manage data

AI has already made an indelible mark on the business intelligence industry, however in 2024 this is going to go a step further. As organisations gear up to adapt to an exponentially larger amount of data, AI is going to provide the much-needed clarity and understanding that organisations need. Explainable AI is easy to understand –  flexible in how it is used and applicable to various use cases, allowing for any member of the organisation to understand the insights that the AI model provides and also how it came to those results. 

The integration of AI in BI tools is not just about automating tasks; it’s about uncovering insights that would be impossible for humans to find. AI algorithms are now capable of identifying patterns in vast datasets, offering predictions and recommendations that guide strategic decisions. This AI-driven approach is transforming industries, from retail where it’s used for personalised marketing, to finance where it’s revolutionising risk assessment.

AI features in BI tools are a game-changer for businesses. Features like predictive analytics, AI-generated reports, and natural language queries are making it easier for users to interact with data and derive valuable insights. These tools are becoming more adaptive, learning from user interactions to provide more relevant insights, which in turn streamlines the decision-making process.

• By 2025, more than 60% of industries will adopt easy-to-understand AI techniques in their business intelligence processes. 
• By 2027, the global AI market will grow at a CAGR of 40.5%.
• 84% of business leaders consider AI as fundamental to drive growth objectives. 

Why is this important? 

Data is always getting bigger, and as more AI models come into the fray, data is no longer just embedded in reports from integrated machines, but also in text, speech, images, and music. If it exists, an AI can analyse it – and at this the amount of data available is so significantly larger that humans will struggle to know where to start, much less to analyse it. 

Trend 2: Natural language processing widens the available data for most businesses

Natural language processing (NLP), a subfield of artificial intelligence, analyses natural language data such as texts, speech, and images; this then allows humans to ask questions of the system using natural language. Going hand in hand with the above trend, NLP in BI means that anyone across the organisation can take insights provided by BI software, and ask a few simple questions to get a few simple answers. It can understand user intent and interpret preferences according to the user, so any question can be answered within a few short seconds. 

Why is this important?

A key issue of adopting any kind of new technology is the widening skills gap in employees; while businesses have the capacity to adopt as many new technologies as their budget allows, finding people who know how to efficiently and accurately use that same technology is a much harder matter, leading to the same issues that made them adopt those technologies in the first place. Without someone to interpret and explain those results, they are no closer to understanding their insights. This effectively makes it a non-issue, as anyone with even basic technical skills can understand NLP-based insights. 

Trend 3: Collaborative BI technologies

Although it’s been a couple of years since COVID-19, the fallout is still very much impacting businesses. During the height of the pandemic, on-premises BI solutions couldn’t withstand the pivot to a largely remote workforce, necessitating the rapidfire adoption of cloud-based BI systems. At this nearly all BI and data analytical elements have been shifted to the cloud, allowing your employees to access the data they need wherever they are. 

• 40% of all workloads are already in the cloud. 
• 45% of consumers consider cloud business intelligence critical. 
• Cloud analytics solutions held 68% of revenue share, and this figure is slated to grow. 

Why is this important? 

The growing popularity of cloud-based systems opens up new opportunities for data analytics. As we move further and further away from the COVID-19 pandemic’s fallout, the changes to business will stay – especially the flexibility of cloud-based solutions. 

Beyond flexibility, cloud analytics are also overall cheaper to run, which means SMEs may find it a more accessible option for business intelligence solutions. Additionally, the cloud-based model can work out cheaper for smaller businesses, as it would allow them to access their data and analytics with a cloud-based service pricing model, rather than creating an internal IT infrastructure from scratch.  

Trend 4: Prioritising data quality governance and security

As data gains importance, so does the importance of its security and governance. Advanced encryption techniques, data masking, and access control mechanisms are being implemented to protect sensitive data. Additionally, with the advent of technologies like blockchain, data governance is becoming more transparent and secure, ensuring that data is not just safe but also ethically managed.

As a result, data quality management transcends basic accuracy. It’s about creating a framework where data is not only precise, but also fit for its intended use. With regulations like GDPR, the need for compliance adds another layer to data governance, making it a strategic priority for businesses. Advanced data governance tools are being leveraged to automate compliance, ensuring data is not only clean but also legally compliant.

Why is this important?

With every passing year, the amount and complexity of data that we have at our fingertips grows considerably, and so do the laws governing the use of that data. While legal ramifications take a longer time to catch up to the pace of technology, it always does eventually, and companies will need to comply with that data if they wish to remain in operation. Additionally, security issues can ruin a company – all it takes is one security breach, and a wealth of data will end up on the internet. As a result, companies need to prioritise both the quality of the data that they have, and maintain high security regulations to protect that data. 

Just how critical is data quality?

For a business to run efficiently, ensuring its data quality is of the highest standards is essential to mitigate operational and decision-making risks. If the data is fragmented, biased, or lacks integrity, it can have a profound impact on the overall business success. Duplicate entries, inaccuracies, or inconsistencies can lead to bias and misunderstanding of the situation for the company, and decisions made can steer the business in the wrong direction

For businesses that need that data for decision-making, this can be catastrophic. 

Trend 5: Democratic data

There are two ways in which data is democratised in 2024. 

The first is the establishment of a data-driven culture: this requires more than just access to data; it requires a mindset shift. Businesses are investing in training programs to imbue their workforce with data literacy, ensuring that every decision, from the C-suite to the operational level, is backed by data. 

The second are self-service analytics tools. Self-service analytical tools are breaking down barriers between data and decision-makers. These tools are becoming more intuitive, with user-friendly interfaces and natural language processing capabilities, enabling users to ask questions and receive insights in plain language. 

Why is this important?

This is fostering a more agile decision-making process, where insights are not bottle-necked in the IT department but are accessible to all who need them. As a result, businesses heading into 2024 and beyond have a much greater portion of their employees involved and aware of the daily decision-making processes, which leads to better operations overall. 

Conclusion 

The BI landscape in 2024 is a blend of technological advancements and cultural shifts. It’s not just about adopting new technologies – it’s about embracing a new way of thinking about, and interacting with, data. By integrating AI, prioritising data governance, and democratising data access, businesses can unlock the full potential of their data, driving innovation and maintaining a competitive edge in a rapidly evolving digital world.

If you are looking for a tech partner to help you navigate the world of BI and data, get in touch with our partners at Cleverbit Software. Their team specialises in guiding businesses through their data analytics and visualisation journey, bringing tangible business insights to the forefront. Find out what a BI solution could do for your business with a no-strings-attached consultation and workshop with their team.

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We’ve been working on trendwatching for the past five or six years. We look at trends consistently in our day to day work, but once a year we compile the top trends in major industries and verticals into a series of documents and eventually into a large book of trends for the year.

In all our years of working on them, we’ve never had such a major shift from one year to the next. Generative AI has taken the world by storm.

What seemed like a soft launch of a new tool by OpenAI at the end of 2022 served as the catalyst for a whole new world, affecting every industry in some way or another.

There seems to be a gold-rush by businesses to accelerate the process of automation, using machines to save on wage costs and the complexities of managing teams. This is, in my opinion, a very short-sighted way of looking at things. If you’re only seeing the rise of AI as a way to save on salaries, then you’re probably looking at it in the wrong way. You might save in the short term, but you’ll be bitten in the backside before too long.

Human behaviour is changing at a much more moderate speed, so we still see overlaps from one year to another around what people expect from businesses, however the dawn of generative AI has brought AI (in all of its forms) to the forefront – making it front and centre on people’s minds as they plan for 2024.

The biggest issue with AI is that it’s moving at such a rapid speed that most people tend to be scared of it. On the one hand you feel like you’re missing out if you don’t keep abreast with everything that’s going on in the industry, on the other you’re overwhelmed by the constant changes, and it makes it kind of tempting to just bury your head in the sand and wait for it all to settle down.

I’m not holding my breath. I don’t think it will settle down any time soon, so my advice to businesses is to really keep on top of things in every way you possibly can.

The revolution is coming and you don’t want to be on the guillotine when the blade drops.

Today we’ll look at what becomes ever more important as we head into a world of constant change.

As every business around you gets access and knowledge of the AI tools around them, you have to work even harder to figure out what makes you special. What makes you stand out, either in a crowded market or in a market that’s being taken over by AI tools.

Humanity

It might seem bleedingly obvious, but as we move into a world of extreme automation, our humanity comes at a premium. There are tools out there that make it easy to personalise messaging at scale. Tools that help us create the mythical “audience of one”, but these are tools. 

Within areas of your business that you can easily automate, using technology makes perfect sense. But in parallel ensure to use the time you’re saving there to create better interactions with your customers and clients. Don’t see the time savings from automation as an opportunity to save money, see them as a great opportunity to give your people more time to build and maintain authentic relationships with your customers.

This will help you stand out from a crowd that is increasingly looking for efficiencies and ways to save money. They’re pushing themselves into extreme commoditisation, effectively creating the perfect environment to be replaced entirely by machines.

Brand

We have been preaching the importance of brand from the inception of the agency, but the need for a great brand and a deliberate brand narrative has never been as acute.

And as you work on your brand, look for the aspects that make you stand out, the elements that add that touch of authenticity that people out there are so desperately looking for.

Don’t hide behind broad strokes statements. Don’t try to be everything for everyone. That time has gone, people can build individual chatbots to do exactly what they want, they expect specialisation, and it will only become more important as time goes on.

People

As we forge ahead with including AI and automation in every aspect of our business, there’s one aspect that we should never neglect or automate parts of, and that’s the relationships that we have with the people around us. 

Your team is, and should remain, one of the aspects that deserves most of your real attention. The people who work with you should always feel as if they’re being treated with decency and authenticity. They are at the core of what makes you unique and, if you neglect them, they’ll quickly find that they can move on.

It might seem tempting to let them do so as you automate more and more, however you have to remember that your clients want to interact with humans, and even if machines can do so much, there’s always an element of bringing everything together that only humans can do (for now, I know).

While it might seem to be extra work to keep them motivated and excited about your brand, they’re the ones who will drive it forward because they can feel an affinity to it (and to you, hopefully) that can’t be felt by machines that are built to automate.

Handmade/humanmade

If we look at the industrial revolution we can quickly see that there will be a great percentage of tasks that will be automated, and this will happen at a much faster pace given the technologies we’re seeing on the market today.

But over the past decade, we’ve seen a resurgence of importance being placed on human-made products and services. This will become more acute as services become increasingly automated. Tasks that can be automated will invariably be automated, but that puts even more value on things that have been made, designed, written, or shot by humans.

Take a long hard look at the aspects of your business that benefit from being made by people, and concentrate on becoming better at them, and in the process becoming better-known for them.

And in the end…

Look at the aspects of your business (and life) that can be automated. Work hard on getting the advantages that AI will give you, but keep one thing in mind: focus on the stuff that you’re good at. Don’t let the AI revolution blind you. Remember what makes you you, what gives your business the edge, and focus on making that better, no matter whether it can be automated or not.

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Blogs about AI are split into two camps:

AI is an excellent tool for productivity. AI can be used to brainstorm. AI can generate images and texts as a precursor to fully fleshing out a creative campaign. AI can be used to create those creative campaigns.

AI is a legal grey area. AI violates copyright. AI should be used sparingly. AI takes jobs away from artists. 

Neither one is fully right. 

The truth is somewhere in between.

How does AI generate imagery?

AI image generation works like this: you write a prompt. 

The machine extrapolates the meaning of every word. 

It gives you an image. 

Here are a few samples that our Head of Brand created as part of a workshop. 

The problem comes after. 

What is copyright law?

Copyright law is the treaty which governs how creative work is treated. There’s no international copyright law, so instead, artists have to deal with copyright law both for domestic and international use. 

The first copyright law was ratified in 1710. Since then, the amount of content that the various laws covered has ballooned – and this includes what is now happening with AI. 

What does AI have to do with copyright?

Ostensibly, AI violates copyright law. 

The manner of how AI image generators are trained means that they learn off datasets scraped from the internet – most of which are protected. The same reason why you can’t just save an artist’s original work and put it onto a campaign falls through when it comes to AI generators, as the ones that currently exist don’t really make a distinction between fair-use artwork and copyright artwork. 

This theoretically means that every AI generated image trained on that dataset is violating copyright law, opening companies up to legal issues down the line. 

Aren’t there laws governing AI use?

The first EU-wide AI law was proposed in 2021. Amendments to the draft were made in 2023 to also determine the use of generative AI. Discussions are currently underway on how this regulation will look, but a brief explanation is this: works created using generative AI will need to be labelled as such. 

Additionally, the restrictions on the use of AI are determined through a proposed classification system that will hinge AI risk on whether it affects human health, safety, or fundamental rights. Theoretically, the lowest tier, minimal, is where most generative AI content will exist, however a separate category exists that will determine the use of generative AI risk on a case by case basis. 

Broadly, Generative AI use in Europe will have to abide by three main rules:

1. Content will have to be disclosed as generated by AI. 
2. The model itself has to be designed to produce only legal content. 
3. Generative AI companies will have to publish summaries of all the copyrighted data used to train their generative AI model. 

There have been some significant pushbacks to this final point, leading to certain AI models such as Google Bard not launching in Europe entirely. 

The United States copyright law is a little simpler: content that is generated with AI is not considered as art created by human involvement, and therefore the art itself does not fall under copyright law protection. Data that was used to train AI models is under copyright law protection, however this has opened up more, not less, legal issues. 

Copyright law cases using generative AI

Here is a list of some of the current copyright law cases. 

• Sarah Silverman, Chrstopher Golden, and Richard Kadrey have sued OpenAI and Meta for using their copyrighted books as training material for ChatGPT. 
• Mona Awad and Paul Tremblay filed a similar suit in California Federal court. 
• John Grisham, George R.R. Martin and other members of the Authors Guild has also sued OpenAI. 
• Universal Music Group is suing Anthropic AI for copyright violation in training its chatbot, Claude. 
• Sarah Anderson, Kelly McKernan, and Karla Ortiz have sued Stability AI, Midjourney, and DeviantArt. 
• Getty AI has also sued Stability AI over the use of its materials to train their Stable Diffusion model. 

The outcome of these cases won’t be determined for a very long time, however it’s clear that the artworks themselves do not appear to be at the heart of the lawsuits. Instead, copyright holders are suing the companies that created the AI models themselves, and this is proving to be a difficult battle to win. 

• In the case of Sarah Anderson, Kelly McKernan, and Karla Ortiz, two of the cases were dismissed, with only Sarah Anderson’s case proceeding, albeit with limited focus. 
• In the case of Sarah Silverman, Christopher Golden, and Richard Kadrey, as well as Mona Awad and Paul Trembley, John Grisham, and George R.R. Martin, a motion to dismiss the case was filed on the basis that the output is not similar at all to the copyrighted works. A counter-claim was filed by the authors against this motion. 

AI companies are also fighting to get the Copyright Office to class its use of datasets as ‘fair use’, which could have further widespread consequences for copyright law. 

What does this mean for businesses?

At this you’re not breaking the law if you’re using AI-generated artworks – provided you are following the legal rules for AI use in your country, which at this stage do not amount to much.

It is very unlikely that legal proceedings against companies simply using the AI tools will make it to court: instead, it’s the AI companies themselves that will have to field this battle. 

That said, there is another issue that small and medium businesses have to keep in mind, and that is the public opinion of AI-generated imagery. Consumers range form apathetic to irritated about the proliferation of AI-generated imagery, and it’s more likely that companies using AI-generated imagery as part of their creative output won’t face a legal reckoning, but a public reckoning: that of their audiences deriding them for the use of AI in the first place. 

What else should I keep in mind?

At the time of this article, there is nothing tangible to state that using AI-generated imagery violates copyright by the company that is using it. Class action lawsuits are being directed towards the parent companies of those AI models. 

That said, this is an issue that’s changing rapidly. We likely won’t see the full scope or scale of laws governing AI until the very end of its initial development cycle, so somewhere around 2024 – 2025. While governments and institutions around the world are working quickly to try and create laws that will limit harm and risk, the world at large was not prepared for this onslaught of content, and it’s taking a longer time than normal to parse through what this means. 

Use AI speculatively. Enjoy its process

We’re keeping an eye out for what’s coming next. 

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