(US & Canada) VIDEO | Generative AI Is Putting Business Intelligence On Steroids — AtScale VP of Product

Elif Tutuk, VP of Product at AtScale, speaks with Robert Lutton, VP at Sandhill Consultants and Editorial Board Vice Chair at CDO Magazine, in a video interview about the impact of generative AI on organizational operations, challenges with generative AI, the need for governance, the balance between automation and human expertise, building relevant organizational skills, and assessing KPIs.

AtScale enables smarter decision-making by accelerating the flow of data-driven insights. The company’s semantic layer platform simplifies, accelerates, and extends business intelligence and data science capabilities for enterprise customers across industries.

Tutuk begins by expressing her views about being in an exciting time. She adds that content creation has become efficient with generative AI and organizations will soon witness the next generation of BI.

Next, Tutuk states that generative AI is putting business intelligence on steroids as content creation does not have to be limited to visualization only. In response to questions, generative AI tools can create data stories in no time, given the right format.

However, the prime challenge with generative AI is the hallucination, as it provides different answers to the same question if asked twice, says Tutuk. To address this issue, she recommends combining generative AI with a semantic layer.

Tutuk maintains that the semantic layer is critical as it provides the governance and business definition that helps generative AI to give better answers. In addition, other factors like data quality, transparency, and all other things related to traditional AI should be paid attention to.

When asked about the need for robust data governance, Tutuk states that the governance challenges of generative AI remain the same as traditional AI, but have been elevated. In this scenario, she suggests organizations have a Data Privacy Officer who would oversee data privacy and compliance.

Further, Tutuk notes that data mapping and classification are fundamental to determining what data contains sensitive and personal information. Also, overall data privacy policies and procedures should be in place with the data access controls, she adds.

Speaking of striking the right balance between automation and human expertise, Tutuk mentions that humans will be working with machines in combination. It is crucial to create an experience where one can interact and provide input so that it gets better with time, she adds.

Delving further, Tutuk talks about knowledge gravity, where part of the knowledge will always come from humans. Therefore she urges organizations to create a welcoming experience for humans, with the semantic layer through easy-to-define business logic.

Furthermore, with generative AI, the system will be able to look at the schemas of the tables and create a base semantic model for humans to augment on top of that. Tutuk believes that there is a definite balance and it boils down to creating an experience where humans and machines can collaborate and learn from each other.

Moving forward, she discusses how organizations can build and nurture skills internally. Firstly, she recommends organizations to conduct a skill gap assessment. This includes understanding if the employees know well about generative AI, how it works, and what they should be aware of.

In addition, she mentions training around data, ethics, and compliance is a must. Further, with automation and efficient content creation, human users will have the chance to shine their creativity.

In continuation, Tutuk affirms that cross-functional collaboration is immensely important for team members. This helps them learn and better understand business and its goals to lead to knowledge gravity.

Tutuk opines that with generative AI, there will be a shift from having technical skills to gaining a better understanding of the business and innovation. In terms of KPI, she asserts that every organization has its own.

However, she suggests organizations apply a product-led and design-thinking approach to creating data and analytics products. According to Tutuk, software development has to be user-centric and organizations need to identify the target users, their specific problems, and questions.

Along with that, an organization must have a clear objective and definition of the minimum viable product (MVP) and determine its KPI that can be measured, she affirms.

CDO Magazine appreciates Elif Tutuk for sharing her insights with our global community.