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What are the quick genAI wins for the data office?

Data leaders need quick genAI wins to demonstrate the power of data and secure increased budgets and backing, but where should they begin?
A member of DataIQ discussing genAI at a roundtable.

Half the battle for CDOs is getting backing and investment for new AI tools, particularly generative AI (genAI), so there is a pressing need to demonstrate their usefulness as soon as possible. There are concerns from business leaders about the use of AI and there is uncertainty about the ever-changing tools available as there is rapid development across every sector.  


Efficiencies are the key to genAI 

Data leaders need to identify the low-hanging fruit within the organisation, and for most businesses this will involve identifying areas ripe for efficiencies and speed. One of the main benefits of genAI is that it can reduce a huge number of manual tasks, adding efficiencies and cost savings to the business by freeing up more time.  

There are numerous examples of different departments experiencing time loss due to manual repetitive tasks, including but not limited to:

  • IT – password resets, status updates, basic diagnostics. 
  • Marketing – content for events, changing images, social media posts. 
  • Operations – rapid recommendations, streamlined configurations. 
  • Customer experience – faster chatbot responses, personalised contact.  

By immediately addressing these common issues and calculating the savings, data leaders can rapidly demonstrate the beginnings of ROI for new AI tools. This approach also highlights the diverse range of uses of genAI and how it can be applied across an organisation. As mentioned, receiving buy-in is one of the difficulties, so being able to provide immediate cost benefits for different department leaders means there is an improved standing of the data office in the business.  


Identify popular interest queries 

Presuming that the organisation keeps a record of all communications coming into the business outside of the designated pathways, the organisation might use genAI to analyse the type of questions asked by users of their service. As genAI can analyse large datasets instantaneously, it can provide a clear list of common queries users are contacting the organisation about. This may identify information that is not as clear as it might need to be on an organisation’s website, highlighting weaknesses through exposing trends that are usually less obvious to the human eye.  

In turn, the data team might then analyse the time saved by the querying user once this improvement is made and exemplify how their journey around the site is improved. Further, this may also provide insight in trends in the type of questions asked; for example, if genAI can quickly highlight that more questions regarding opening hours are asked at the weekend, the organisation might chose to display that information on a clearer section of the website at during that time period and therefore reduce the amount of queries by X%. The querying user will then have more time to interact with the organisation in the desired manner, in comparison to searching fruitlessly through a dropdown list of loosely related frequently asked questions. 


Content is King 

GenAI’s impact on content creation is a highly contested area; while it is technically able to create content in certain styles through condensing lots of information down into a desired word-length, the quality is often poor and the readability subpar. It remains as important as ever to fund creative jobs that require human experience, personal flair and knowledge of the brand when creating content as there is currently no replacement for human creativity. However, the data team can use genAI to their advantage by using it to maximise search engine optimisation (SEO) to benefit those creating content for their business.  

As a continuation of the suggestion above, genAI can provide the fundamental information to help data teams spot new ways to optimise their content. For example, genAI can provide the most up-to-date search terms for content inclusion, as well as keeping the creator informed on any updates to SEO rules and crawling from different providers. This is a quick win that can help show the power of data to teams outside of the data office, such as marketing and sales, and will improve the data culture within a business by making data tools understood and accessible to those without a data background. 

Similarly, genAI can be used in advertising campaigns to multiple specific audiences by changing the tone of the message depending on which site it appears upon, and therefore what audience it will reach. As an example, a retailer could set up a seasonal advertising campaign for one audience and then have genAI provide information about how different audience segments respond best to advertising campaigns. The advert can then be updated accordingly to provide the best outcome for all target audiences and distributed to the areas where it will be best engaged with for the different demographics. 

Data-driven decisions are essential when it comes to considering search engine rankings, marketing scheduling and the type of information available to specific demographics or, indeed, specific users. Without data-driven insights, the utilisation of these groups will always remain diminished. Beyond this quick win, genAI can be used to create customised content including recommendations and different pathways into the organisation – this is ideal for channelling users and visitors to a specific product or upsell.

A data focus is necessary for the whole genAI journey, as genAI can be deployed to investigate the effectiveness of its own suggestions and enhance the way it is utilised. This will continue to improve as the use of genAI expands and the capabilities of the tools available today will likely be a fraction of what will be possible in another 12 months.  

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