If Artificial Intelligence is the future, its creators must be multifarious in all aspects. This ensures that the responsibility fulfilled by the AI considers a roundabout perspective rather than a monotonous attitude. Reinforcing the strategy of enabling assortment in the industry demands the active participation of innovators to embrace the opportunities and stand out at the helm of advancements.

However, there are many exemplary women leaders at the forefront of AI today. It is a matter of fact that women have always provided a different perspective and approach, and they have established themselves substantially in enhancing the algorithms, particularly in the AI industry. They also serve as role models for future generations of AI leaders, ensuring innovations and a comprehensive AI community.

One such coherent personality is Shaily Verma, Director of Digital and Data at DAMAC Group. Shaily is a high-impact & result-driven internationally acclaimed thought leader with a solid track record of orchestrating growth and leading strategic digital initiatives.

Shaily believes in positive impact-based working models and has created AI-enabled micro experiences. With 16 years of experience in tech, she is focused on developing digital strategy and data analytics for businesses, with a primary focus on Customer centricity. She has been developing strong digital center of excellence teams that keep up with the fast paced, ever-changing environment and deliver high quality solutions through data science, digital technology implementations, and AI.

Shaily defines herself as a ‘Thought Leader of ‘Digital analytics for impact’.’ She has worked with Martech/Adtech/CRM/data activation strategy/business strategy/product strategy/ consumer insights. She is actively assisting in the development of high-impact data products & data science teams that are operationalizing actionable insights to improve business processes.

Let’s dive into the mesmerizing odyssey of a resolute leader.

Journey as a Business Leader

Shaily started her journey as a pure techie, a computer engineer from one of the Fortune 500 tech organizations as a software developer. And gradually, she began to lean toward her first love of mathematics via seeing the numbers in data analytics and computing to make a difference in businesses.

Working and learning in various digital, data, and business roles, Shaily has been given the position to roll out departments as the center of excellence for Data Analytics and AI, which she has been doing in a conglomerate for many years. Her main interest is mentoring the team to identify opportunities to make business automated and more profitable. Insightful decision-making is the primary goal of her team.

The key specializations of Shaily are identifying and implementing AI-driven projects to make the world smarter, faster, and more automated. She is a committed leader who delivers results through teams. Her leadership style is inclusive, collaborative, and team-focused, delivering customer-obsessed results.

Subduing the Odds

Data illiteracy in the organizations, lack of digital buyins, completing the loop of feedback of data to the platforms, and lack of the right talent to fit the job, are some of the challenges that Shaily faced in her career. Nonetheless, a solid strategy is what helped Shaily. It gave her visibility on the positive impact on the business and helped her team to overcome multiple stages of challenges.

Shaily adds, “Advocating for the right data collection for the adoption of AI-enabled systems has been the game changer.”

Another challenge that Shaily faced on her way to success was culture change.

She tackled the notion of different cultural implications by setting up weekly data science readouts while also setting up one business data resource in each business. It helped to spread the use of centralized data in the decentralized working operations model. This created a safe environment to get positive reinforcement and some great feedback from peers.

As an exemplary business leader, she also created a safety net among the teams so that ideas could flourish and can be adopted without hesitations and ego. She also inspired staff to have multiple skills apart from the main specialization to constantly push the boundaries while providing executive goals exposure.

Shaily remarks, “If you connect the team to the bigger goals and executive agendas and keep them informed on the futuristic aspirations, Team elevates their thinking within their domains.”

A catalyst in Creating Strong Data Culture

Shaily states, “Mass adoption is the reflection of correct solutions and the addressing of needs. Tech enables AI data solutions to not only identify the real needs in business but also help in solving effectively and efficiently.”

Shaily helped in making the process multiple folds faster, smarter (auto-output) AI-enabled chatbots, AI Robo callers, Speech to text NLP based interpretation, Algorithmic/ML-based behavior analyses, Transaction analyses, segmentations, and predicted insight which helps in generating incremental RoI. Data-enabled customer interaction, AI-enabled apps, along with Blockchain smart contracts and Defi, are other use cases as well.

Bringing equality is one of Shaily’s main agendas.

“As you see in the stats, less than 1% of women are in the highest decision-making positions in the Middle east. I was one of the 6 girls in my computer engineering class of 66 students. Thankfully the stats are changing in India and Nordic countries, but they also require to be changed in other parts of the world,” expresses Shaily.

She also believes that every organization must be data driven, and the decision-making should have enforcement to the use of data insights. Understanding AI but using it with ethics removes the unconscious data biases while using algorithms and predicting based on historical data, which might be completely biased based on major events in the world.

Shaily concludes, “Avoid investing major time in moving data physically; save time using cloud-based solutions which are also AI-enabled. Focus on improvement of quality and accuracy of data; as they say, garbage in, garbage out!”

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