How Adobe’s GenAI Agents and No Code AI Makes Data Analytics Accessible to Everyone

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Challenges in the World of Analytics

In a world with rising access to and volume of data, knowing how to manage and process it effectively becomes a competitive advantage for organizations. While most companies say that their usage of and investments in analytics and AI is on the rise (McKinsey 2024), the capabilities of business are mostly not equipped to handle the complexity that comes with it. Two main causes for the lack of these capabilities are: 1. missing data and AI literacy (Data Camp 2024) of non-data/AI oriented employees, and 2. the lack of skilled specialists, e.g. data analyst or data scientists, who can compensate for the lack of organizational data and AI literacy (PwC 2024).  

For leaders trying to bring their digital products to market, validate product/market fit and gather millions of data points, these limitations are a serious risk. It leads to a situation in which companies can’t get the insights from their data and cannot train models for their purposes as fast as required. Not only is access to data processing technologies inhibited, but experts also warn that most business decisions are being made based on inaccurate data or biased assumptions.  

Source: Itamar Gilad 2018 

According to Itamar Gilad, an Ex-Product Manager from Google and Microsoft, most data points product teams use to decide what features to develop and launch, have a low confidence level in predicting success. Examples for such low-confidence data points can be ideas coming from experts or insights gained from market studies, which were not further evaluated which real data from your user base. The only true predictors of how well users will respond to an innovation is data collected from your users through methods such as A/B testing results. 
So, if all of this is true, how can we make access to tools and understanding of data easier?  

Introducing GenAI Agents and No-Code AI 

Many CEOs and experts (e.g., the Adobe CEO) envision a future in which AI “augments human ingenuity” and does “not replace it”. Research shows that AI can help humans reduce bias when analyzing data and improve process efficiency. Especially ‘no-code’ approaches to making data and AI technology can significantly improve innovation capabilities because it democratizes AI, as shown in research by Adobe and Siemens (Adobe/Siemens 2024). 

Inside Adobe Experience Platform solutions like Customer Journey Analytics, GenAI already supports users in improving their understanding of the tool through prompt-based interaction. 

Source: Adobe 2025 

Another example of the educational power of AI is Natural Language Generation (NLG), which is used in Customer Journey Analytics to automatically describe the most important insights from a graph in bullet-point style, as show in the screenshot below.

Source: Adobe 2025

 This is especially helpful for those stakeholders that have limited experience in analytical thinking and data interpretation, as GenAI can help debias the interpretation with user-tailored explanations of the analysis results. These advancements will soon benefit users in an increasing number of use cases in CX management with Adobe’s Agent Strategy (Adobe 2025). 

Your Path to Improved AI and Data Literacy

One thing is to have the software, another thing is to be able to use it. Being data and AI literate is one of the fastest growing and most sought-after skills. To develop your skillset, Adobe offers multiple ways to improve your capabilities to learn how and when to use analytics, enable agents or onboard and structure useful data within the Experience Platform and Cloud products. The focus is to bridge the gap between your goal and the technology to realize value.  

At learning.adobe.com, companies can book individual sessions and view on-demand content on analytics, data platform and GenAI or get a subscription to consume all educational content. For example, users can take 1 to 3-day classes which will give them a better understanding of the tools, including the AI capabilities. The classes are based on demos and interactive exercises that turn knowledge into action. For AI, I’d recommend the Target course “Automate and Personalize” or the short course on “Customer AI”. Additionally, feel free to explore the Experience League. 

Autor: 

Mario Truss is Technical Training Consultant with expertise in analytics, AI and personalization. During his career, he worked as RT-CDP Expert Solution Consultant Expert with a focus on intelligent services and as a product owner for one of the biggest Atlassian and Google partners in Germany.