It's almost been a year since Chat GPT made its debut. Over the past year, AI has shifted from a concept only the techies thought about and directors explored in films to a reality of our everyday lives. The past year, in particular, has highlighted the significant transformation it can bring to white-collar workers.
We asked our guests at our first AI event six months ago to raise their hands if they had used Chat GPT - only a few hands were raised. However, our recent AI event on Tuesday felt like a different audience. Many of the same people, but with a different outlook on how integral AI is becoming to their overall marketing and communications strategy.
In this session, we delved into the various use cases of AI in the industry, explored the opportunities and risks it presents, and discussed the role of data in developing AI strategies. Most importantly, our panellists spoke about what's next for 2024. In this article, we will share the key insights and takeaways from our discussion.
- Financial services, marketing and communications all fall within the top sectors forecasted to be heavily impacted by the advent of gen AI.
- It is crucial for organisations to review their data sources and uses, which requires classification and cataloguing of data.
- To successfully scale the use of AI in 2024, organisations need to prioritise undertaking a data strategy to create a robust AI strategy and address ethical and regulatory considerations.
The impact of AI in financial services marketing and comms
Katherine Shenton, Global Marketing Director at QuantumBlack AI by McKinsey, one of our panellists, shared on stage some research from McKinsey showing that the industries which rely most heavily on knowledge work will see the highest impact from gen AI. They found that gen AI will add up to 5 per cent of global industry revenue to the banking sector, one of the top three to experience that level of value, making financial services an incredibly exciting area for advocates of gen AI.
Furthermore, according to McKinsey data, around 75 per cent of the value that generative AI can deliver falls across four areas, including marketing and sales, customer operations, software engineering, and R&D. With that in mind, it's crucial to get more of an understanding of how gen AI can actually make this impact.
It's all in the data
Generative AI does not escape the age-old saying within machine learning, "garbage in, garbage out". With Chat GPT having scraped and trained on information from some sources not always deemed reliable, the output can sometimes cause speculation. Its ability to hallucinate and portray untruths as reality can be worrying, considering its universal accessibility and lack of regulation.
These issues with generic large language models like Chat GPT mean that as a business, you are probably considering how to start developing or building upon your own AI Strategy. At our event, Blaine Carper from Snowflake eloquently explained, "If you do not have a data strategy in place, there is no way you can even start to approach an AI strategy." The first step in embarking on this digital transformation journey is understanding what data you have, getting all of that data into one place, gaining a deeper understanding of what data is just noise versus what is useful and then cleaning and cataloguing that data.
The next step is understanding your use cases to be able to build a gen AI product that actually optimises and improves your team's productivity. AI is relevant to every department that sits in an organisation, and understanding its current use-cases is vital to exploring its possibilities. Once you have automated the mundane, you can move on to thinking through more high-leverage cases.
Tom Coombes, our CEO and founder, shared how, at Cognito, we are leveraging experts in data science, decision theory and AI to make sure that when we deploy AI, it makes sense. We are starting to run data studies with our experts to leverage proven methods, ensure that we understand our sources and use cases, provide quality in to get quality out, and get our cataloguing correct so that we can focus on creating the right AI strategy. We are now starting to offer these services to our clients. Please get in touch with firstname.lastname@example.org if you are interested.
Keeping the human in the loop
The question which still lingers in the news or amongst friends when sat in the local pub is, "Will gen AI take my job?". Interestingly, white-collar workers have been impacted the most from the advent of gen AI. However, gen AI and the white-collar worker are set to have a flourishing relationship if businesses seek productivity gains and growth instead of using it to reduce headcount.
In Marketing and Communications, humans play a crucial role. They serve as the vital safeguard against gen AI hallucinations and provide an extra layer of unmatched human judgement. By formulating an AI strategy that prioritises the concept of "Human-in-the-loop", businesses can establish powerful systems that allow both humans and technology to interact continuously and seamlessly.
Embracing the "Human-in-the-loop" approach means recognising that while gen AI possesses remarkable capabilities, businesses will thrive more when AI works in conjunction with human expertise. Rather than replacing humans, gen AI can be harnessed as a powerful tool to augment and amplify the abilities of marketing and communications professionals.
What does the industry need to consider and how can teams prepare for 2024?
In 2024, the industry needs to consider several key factors as it prepares to scale its use of AI. Firstly, organisations must focus on building a strong foundation for AI implementation. This involves developing robust data infrastructure and governance frameworks to ensure the availability and quality of data required for AI models. Additionally, businesses need to invest in talent acquisition and upskilling to cultivate a workforce that can effectively leverage AI technologies. Collaborating with AI experts and partnering with technology vendors can also provide valuable insights and support during the scaling process.
Moreover, teams should prioritise addressing ethical and regulatory considerations associated with AI. As AI becomes more pervasive, ensuring transparency, fairness, and accountability in AI systems is crucial. Organisations must proactively assess potential biases, privacy concerns, and the impact of AI on individuals and society. Engaging in responsible AI practices and adhering to relevant regulations will help build trust with stakeholders and mitigate potential risks.
Furthermore, in 2024, the industry will witness an increased focus on democratising AI. While larger organisations may have already adopted AI, the challenge lies in enabling smaller businesses to follow suit. This requires making AI more accessible, affordable, and user-friendly. Cloud-based AI platforms and pre-built AI solutions can play a significant role in empowering smaller businesses to leverage AI capabilities effectively.
By considering these factors and adequately preparing, organisations can navigate the transition from AI adoption to scaling effectively. This will enable them to unlock the full potential of AI, drive operational efficiency, and stay competitive in the ever-evolving business landscape of 2024.