News Analysis
The Gist
- Agentic AI enables real-time insights. Autonomous agents help unify enterprise data and generate trusted analysis, even for non-technical users.
- Marketing and CX leaders face data pressure. AI has amplified the need to be data-driven—but confidence and access remain challenges.
- Education is key to Agentic AI success. Without executive support and data literacy, adoption of Agentic AI may stall before it scales.
Three and a half years ago, I shared in CMSWire how Self-Service BI was becoming a trend for business leaders, particularly CMOs and their teams, to obtain the data needed for marketing decisions.
CIOs at the time shared several drivers for self-service BI, with the primary being to reduce the cycle time for decision-making. The aim was to make data and analytics teams less of a bottleneck, allowing businesses to respond at the speed of today's market.
The concept of information democracy had expanded the audience needing access to data, but the inability to provide line-of-business users with the information they need, when they need it, created a backlog. The goal was to make decisions when they were needed, and this required quick and easy access to the right data at the right time.
As Frances Frei and Anne Morris state in "Move Fast and Fix Things," the most effective leaders solve problems at an accelerated pace while also taking responsibility for the success and well-being of their customers, employees and shareholders.”
CIO David Seidl suggested at the time that “a highly usable data portal or access tool, including data discovery and contextualization, is critical for more casual, non-power users. This is the real destination of self-service BI in the long term, with a stop at power users along the way.”
However, the solutions at this time, such as data catalogs, did not go far enough. The need for quick and easy access to the right data at the right time remained a critical challenge for businesses aiming to make timely and informed decisions.
Table of Contents
- Marketing, CX Leaders Want to Be Data-Driven in Age of AI
- Agentic AI to the Rescue?
- Parting Thoughts: Why Agentic AI Matters for Marketing Leaders Embracing Self-Service BI
Marketing, CX Leaders Want to Be Data-Driven in Age of AI
Recent research from Salesforce Tableau highlights the increasing stakes for data-driven decision-making among businesses and their leaders. Marketing and customer experience leaders are particularly under pressure, with 93% of customer service leaders and 83% of marketing leaders stating that the rise in AI has heightened their need to be data-driven.
At the same time, amid below-average rates of business confidence, an uncertain economy, and frequent headlines of cost-cutting, businesses require more accurate and reliable insights to guide deliberate and agile decision-making. However, less than half of business leaders say their data strategies—how data is collected, managed, stored, and accessed—fully aligns with their business priorities.
“There is an increasing amount of pressure on business leaders to use data in today’s hyper-competitive environment,” says Southard Jones, chief product officer of Tableau. Tableau’s research finds that three-quarters of business users feel pressured to prove their value with data, with 57% feeling in competition with their colleagues to back their arguments and claims with data—a sentiment even more common at the executive and VP levels.
Despite 63% of business leaders needing to find, analyze and interpret data on their own, 54% are not fully confident in their ability to do so. Trust in the data underpinning these decisions is falling, and many leaders do not feel equipped to find, analyze and interpret the data they need in an increasingly competitive business environment.
Issues such as data literacy, relevance, reliability, timeliness, accuracy and completeness are significant challenges. This reflects that only a small number of organizations have truly industrialized their data.
Related Article: Could Salesforce-Informatica Acquisition Create a Data Queen?
Agentic AI to the Rescue?
According to Jones, fragmented enterprise data and complex analytics tools are common obstacles that leaders face, significantly hindering confident decision-making. His company rolled out a solution today that officials say features Agentic analytics that unify data and empower AI agents to proactively deliver trusted, real-time insights to everyone, enabling data-driven decisions for everyone – even those who do not consider themselves "data people." Jones believes that agents can find insights humans missed, identify patterns in data that may have been overlooked, and help people reason.
From my research, Agents integrate structured and unstructured data with workflow logic to create autonomous agents capable of executing complex tasks, including data analysis. They allow users to ask questions of their data in natural language, making data accessible to a broader audience. This aligns with what Elisa Farri and Gabriele Rosani of Capgemini state in their book "Generative AI for Managers": “GenAI can become a co-thinker for managers in organizations, aiding in problem-solving and decision-making.”
The potential of Agentic AI is vast, including reading and cleaning data, translating data into visuals, and extracting insights—this should matter to CMOs who need to use data to personalize customer experiences, understand customer behavior and preferences, and make data-driven decisions to improve campaign performance and ROI.
Related Article: The Rise and Impact of Agentic AI: Transforming the Human Experience
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Parting Thoughts: Why Agentic AI Matters for Marketing Leaders Embracing Self-Service BI
The rise of Agentic AI marks a significant evolution in self-service BI, offering a promising solution to the challenges faced by marketing leaders in today's data-driven environment. By integrating structured and unstructured data with workflow logic, Agentic AI empowers autonomous agents can deliver real-time insights, enabling confident decision-making for everyone, even those who do not consider themselves "data people."
Here are my big Agentic AI takeaways:
- Agentic AI can unify fragmented enterprise data and empower AI agents to deliver trusted, real-time insights.
- Education and literacy are crucial for the successful adoption of Agentic AI, as many leaders still struggle with data literacy and confidence.
- Use of Agents like earlier business intelligence needs to start at the top. Otherwise, it will not happen quickly and pervasively.
However, the adoption of Agentic AI is still emerging, and data leaders must prioritize education and literacy to fully realize its potential.
