The transformative power of AI is undeniable, and it’s here to stay.
There are very few of us in the environmental and energy sector can say that we are not aware of the developments taking place in the area of Artificial Intelligence or AI. Whether it be the roll-out in its use in the workplace, or indeed closer to home on your mobile device as a way to improve your internet searches, AI’s influence is spreading far and wide and shows no signs of slowing down.
Those of us operating in sectors such as marketing and market research shouldn’t assume we are immune to such developments. As clients strive for competitive advantages, generative AI tools such as Chat GPT, DALL-E, Claude and Gemini are proving increasingly popular. Utilising the same learning approaches that have already revolutionised long range weather forecasting, AI deployment is expected to continue to advance.
Boarder technological developments are assisting AI’s adoption
Yet, it’s not only the availability of these tools that’s driving AI adoption. Broader advancements in computing power, cloud infrastructure, machine learning algorithms and real-time data processing capabilities are creating new avenues for analysing and interpreting information. Coupled with the familiarisation of simpler AI tools like voice assistants and chatbots, these technological strides are making AI an increasingly attractive prospect for businesses worldwide.
Using AI is not without its challenges
According to research undertaken in 2022 some 35% of companies were already using AI while a further 42% were exploring its use. Whether it be for predictive maintenance or data analytics, both figures are likely to have increased subsequently and illustrate an increasing appetite to benefit from AI in its various forms.
However, despite this growing enthusiasm for AI, there are considerations that cannot be ignored by those involved in marketing and research. These include:
- The fact that understanding how AI-based decisions are made remains opaque.
- The issue of how AI will affect the use of traditional, and trusted, methodologies.
- Potential biases rooted in the data used to train AI models and algorithms.
- Its impact on traditional tasks like data analysis and interpretation, which are foundational to delivering value for clients.
Leading Edge is already harnessing AI to support client projects …
Like many companies operating in marketing and research, we’re observing these AI advancements closely, particularly the speed at which new capabilities are being released. Change, and the pace of it, remains our main concern. The evolution of specific generative AI tools has been fast-paced, with each update promising more precision and functionality.
Although waiting for the “next big release” is tempting, we recognise that the current capabilities of AI can already add value to the support we offer clients, particularly in data analysis.
… with qualitative analysis offering clear value
Recently, we introduced AI-driven analysis as part of our B2B customer research support to supplement verbatim comments that are shared on an Excel spreadsheet. Capturing core insights from what is often detailed customer feedback, AI is able summarise key conclusions from the research as well as highlight potential areas for improvement.
Limitations and restrictions mean AI may not be suited for all projects
That said, AI still comes with certain limitations. Generative AI, while continuously improving, is not foolproof in its data interpretation abilities. The way it “learns” is based on a myriad of datasets from diverse users. Although this improves results over time users need to bear in mind possible questions about accuracy and decision-making transparency.
Beyond the fact that AI will continue to be a ‘black box’ when it comes to understanding how it interprets data, other issues also need to be considered. Most notably, are complications associated with the EU’s General Data Protection Regulation (GDPR). In cases where clients stipulate no external processing of data, AI integration may not be possible. Even where permissible, you still need to ensure that you are on the right side of GDPR.
In using AI analysis, we prioritise GDPR compliance, ensuring all data sent to AI tools is fully anonymised, with personal, organizational, and location-based information removed.
Future applications in using AI are only set to expand
Despite the fact that use of AI comes with a health warning, its growth to support market research is inevitable with potential for use in both B2C and B2B applications.
Providing caution is taken in how results are interpreted, generative AI is already proving to be a dependable asset for researchers in the area of analysis. As tools become more sophisticated and widely accepted, we anticipate its increased role in data collection. How fast steps in this direction are taken will not only be based on the increased sophistication of tools available but also their acceptance by end users. Regardless of the speed of this process, it is clear we are in a transformational stage in the use of AI.
Chris Hadley
Lead, Environment and Energy
