With careful planning, ethical considerations, and ensuring human oversight is maintained, AI can have huge market research benefits, says Lorenzo Livi of the Open Institute of Technology

To market well, you need to get something interesting in front of those who are interested. That takes a lot of thinking, a lot of work, and a whole bunch of research. But what if the bulk of that thinking, work, and research could be done for you? What would that mean for marketing as an industry, and market research specifically?

With the recent explosion of AI onto the world stage, big changes are coming in the marketing industry. But will AI be able to do market research as successfully? Simply, the answer is yes. A big, fat, resounding yes. In fact, AI has the potential to revolutionise market research.

Ensuring that people have a clear understanding of what exactly AI is is crucial, given its seismic effect on our world. Common questions that even occur amongst people at the forefront of marketing, such as, “Who invented AI?” or, “Where is the main AI system located?” highlight a widespread misunderstanding about the nature of AI.

As for the notion of a central “main thing” running AI, it’s essential to clarify that AI systems exist in various forms and locations. AI algorithms and models can run on individual computers, servers, or even specialised hardware designed for AI processing, commonly referred to as AI chips. These systems can be distributed across multiple locations, including data centres, cloud platforms, and edge devices. They can also be used anywhere, so long as you have a compatible device and an internet connection.

While the concept of AI may seem abstract or mysterious to some, it’s important to approach it with a clear understanding of its principles and applications. By promoting education and awareness about AI, we can dispel misconceptions and facilitate meaningful conversations about its role in society.

Coming into its own

Much of marketing is data processing and analysis, and this is where AI really comes into its own. At handling vast amounts of data efficiently and extracting valuable insights, AI is in its element, it excels. 

With machine learning algorithms, and vast data sets at its electronic fingertips, AI can sift through a huge diversity of data sources, including, but not limited to, social media, customer reviews, and sales data. It will also be able to identify trends, preferences, and market sentiments, and package these as easily assimilable findings for marketers. It is also a great help when it comes to market research due to its inbuilt automation and efficiency. AI technologies can be set to automate repetitive, time-consuming, but necessary tasks that make up market research, such as data collection, segmentation, and analysis. By automating these processes, AI frees up human researchers to focus on more strategic tasks, increasing efficiency and productivity in gathering market intelligence.

AI is not limited to data collection and analysis, though. It also has predictive capabilities. AI-powered predictive analytics can analyse gathered data and be used to forecast market trends, consumer behaviour, and demand patterns with greater accuracy than traditional methods, and with greater speed. By swiftly analysing historical data and real-time market signals, AI algorithms can anticipate future market shifts, enabling businesses and marketers to make informed decisions and stay ahead of competitors who are not using AI.

AI will also be able to personalise adverts, too, tailoring them for audiences, based on the findings of its research. The better you can recognise the needs of a stakeholder, the better you are able to offer them something they want or need. In terms of automation, scalability, and human-improved abilities, AI can kickstart a fundamental change in marketing.

What belongs to who?

However, it is not all sunny vistas for marketers at the dawn of this new technology. While AI offers significant potential in market research, its adoption can also pose several challenges and potential problems, in terms of data privacy and ethics, bias and fairness, interpretability, and it may well lead to an over-reliance on AI across the industry, especially initially; a kind of AI arms race to use the tech to impress clients that, ultimately, leaves out the canny human element to the detriment of results and innovation.

AI relies heavily on data, vast tracts of data scooped up from the internet and elsewhere. Much of this data belongs to people, which raises grave concerns about privacy, security, and ethical use of personal information. The speed at which the technology is improving, and the power of the mega-corporations often helming AI projects, adds to concerns over data and privacy. 

Improper handling of sensitive data or biased algorithms can lead to privacy breaches, discrimination, and regulatory violations, leading to unethical action and damaging trust with consumers and stakeholders. AI algorithms may perpetuate or amplify biases present in the data they are trained on, leading to skewed insights or discriminatory outcomes, concerns which are rightly front and centre in modern society. Biases in market research can result in inaccurate conclusions, unfair treatment of certain demographics, and missed opportunities for inclusive decision-making.

Relying solely on AI for market research can also lead to a fundamental and damaging loss of human intuition, creativity, and critical thinking to the people and companies working with AI. Human oversight is crucial to interpret complex findings, insert creativity and original thinking, validate AI-generated insights, and contextualize data within broader business strategies and objectives. AI algorithms can be complex and opaque, making it challenging to understand how they arrive at their conclusions. 

Over-trust in these findings, and, concomitantly, a lack of transparency and interpretability can hinder trust in AI-generated insights and lead to heavy scepticism among decision-makers, particularly in highly regulated industries or when making critical business decisions.

All of these less-than-ideal issues and consequences of an overreliance or over-implementation are very important problems with significant impact on our society, and for the world of marketing (and all those influenced by it). In other words, it all requires careful consideration from the major players in the field and decision makers at every level. The negative consequences of integrating AI into market research, if not managed properly, include inaccurate insights due to biased data and over-reliance on AI outputs, which could easily erode consumer trust through privacy violations and ethical missteps that create big headlines, leading to legal repercussions and reputational damage. As marketing is all about building reputations, this would be a tremendous corporate faux pas and could sink businesses.

Perpetuating inequality

In a world increasingly concerned about equality, increased inequality could occur if AI perpetuates or dramatises current biases or interpolates biases of its own, leaving certain groups disadvantaged. This is an ethics issue, and one that marketers need to ensure is stamped out at the outset of any use of AI, lest their results contribute to inequality and discrimination.

Also, an ethics issue is the use of AI leading to job displacement and severe skill gaps, which may arise as roles become automated through the adoption of AI and jobs are replaced, or when the technology advances and its use requires intensive retraining programmes. Security risks such as data breaches and system vulnerabilities also pose significant threats. All data that streams from A to B is subject to potential hacking and the interference of malicious actors. 

Addressing these concerns requires a balanced approach, one that comes from serious thought and reflection, and which integrates technological advancement with ethical considerations, human oversight, and a focus on maintaining consumer trust and data security.

Time is of the essence 

Ultimately, this technology is well on its way to being rolled out, and marketers and market research experts will need to get to grips with it at speed. The main issues with it being used unethically or leading to unethical results would be if the issues with it got out of hand. And that will happen no matter that, as with any other big revolutionary technology in our history.

 It is how we deal with it getting out of hand, deal with the fallout, and create the necessary changes in order to better our use of AI that will lead to it being a super-effective and ethical tool at our disposal.

Integrating AI into market research will be worth it for most organisations, provided they can manage the associated challenges effectively. The potential for enhanced insights, improved decision-making, increased efficiency, and competitive advantage makes it a valuable tool. However, careful planning, ethical considerations, and ensuring the right balance between AI and human oversight are crucial for maximising its benefits. 

About the author
Lorenzo Livi is Program Head and Academic Director at the Open Institute of Technology.