(US & Canada) VIDEO | Cross-Collaboration Is a Key Ingredient for AI Success — Brown-Forman Director of Advanced Analytics and AI Strategy

Amit Parulekar, Director of Advanced Analytics and AI strategy at Brown-Forman, speaks with Nayla Sidhoum, Client Director at AHEAD, in a video interview about the three stages of building an AI strategy, managing AI use cases, talent upskilling, and the organizational impact of AI.

The Brown–Forman Corporation is a major spirits and wine business based in the U.S.

Speaking about building AI strategies at the company, Parulekar discusses a three-phased approach.

1. The first phase starts with observing and describing, which involves a complete and comprehensive understanding of AI.

This includes its usage, capabilities of AI systems, and its risk components, through building a robust AI systems repository.

2. Second comes the discovery stage, which includes thorough assessment and identification of new use cases through product discovery and risk assessment framework.

Parulekar opines that the success of product discovery hinges on creating shared awareness among business and IT around AI’s limitations and opportunities. He stresses carrying out awareness sessions and continuously evolving risk governance framework.

3. Once the use cases are identified, comes the last stage of building the new use cases, and scaling those across the enterprise.

When asked how use cases are being managed at Brown Forman, Parulekar discusses adopting a two-pronged approach:

  1. Allowing use cases to evolve organically

  2. Discovering new use cases through AI awareness programs

2. Discovering new use cases through AI awareness programs

Delving further, he mentions building a diverse portfolio of AI projects through a responsible AI innovation framework. The organization balances between quick wins and long-term initiatives. The advantage of quick wins is that it enables business users to comprehend the power of AI, ensuring complete alignment of AI with business strategy.

As a long-term commitment, Parulekar affirms buying things off the shelf, which portrays the dedication to drive sustainable innovation and commitment to push AI boundaries. Adding on, he maintains that Brown-Forman maintains the balance between quick win initiatives by building in-house models for optimization and combining them with commercial off-the-shelf applied AI.

When it comes to AI success, it is critical to build, support, and sustain talent. Therefore, Parulekar mentions creating two pathways for digital upskilling:

  1. Upskilling pathway for existing data scientists to keep up with evolving technologies

  2. Training business users to create analytic ambassadors in each business area

The first pathway has helped the organizational data science team learn about popular AI frameworks, and utilize the same. The second pathway, Parulekar says, is an immersive program with AI workshops designed to empower business professionals from different backgrounds to apply AI in the business setting.

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(US & Canada) VIDEO | Cross-Collaboration Is a Key Ingredient for AI Success — Brown-Forman Director of Advanced Analytics and AI Strategy

Commenting further on talent upskilling, Parulekar notes that Brown-Forman is a people-focused company and is committed to upskilling. He ensures having a designated training budget allocated to the data science team that allows them the flexibility to attend conferences and grow into AI engineers.

To address the gaps in resources, he mentions establishing strategic partnerships with various talent providers, to scale up or scale down resources, depending upon the initiative.

Reflecting on the impact of AI at Brown-Forman, Parulekar states that as an industry, one of the critical ingredients for the success of AI initiatives is cross-collaboration. Creating the AI culture is the key to success, he adds.

AI can be applied in every area of the company, says Parulekar. The two significant benefits of AI lie in its ability to enable the creation of new products and drive operational efficiency and workers’ productivity.

Furthermore, he discusses applying AI in different settings like the optimization of supply chain logistics and predicting consumer preferences of fine-tuning and production processes.

In conclusion, Parulekar states that while AI can be a game-changer in the spirits industry, organizations must be cautious while applying the technology. He urges organizations to invest in the right technology, to leverage AI to make the industry more agile and competitive.

CDO Magazine appreciates Amit Parulekar for sharing his data insights with our global community.

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