Empowering Safety and Efficiency Through AI

About the role:

As a product expert at Motive for over six years, Afsheen focuses on building robust AI models that enhance productivity, safety, and sustainability across logistics and fleet management. Collaborating with cross-functional teams, she ensures our AI solutions are accurate and scalable, solving real-world challenges, and promoting responsible practices.

Motive’s unique AI approach

Motive’s AI approach emphasizes real-world application for the greater good. We integrate AI capabilities into fleet management solutions, enhancing safety and efficiency. Our models provide actionable insights that enable sound decision-making, benefiting both businesses and individuals.

What sets Motive apart is our commitment to accuracy, scalability, and continual evolution, ensuring our AI adapts to customers’ needs. By merging AI with deep expertise, we tackle critical challenges and promote safer, more efficient operations for our customers.

What are the industry’s biggest misconceptions about AI? 

Afsheen stated one of the major misconceptions about AI is that it’s a one-size-fits-all solution. In reality, AI requires customization to meet the unique challenges of each industry; off-the-shelf solutions often fall short.

Another myth is that AI delivers immediate results. Implementing AI is a gradual process involving quality data collection, model training, and continuous fine-tuning. Real value comes from careful integration and evolution over time. Meaningful results require patience, ongoing adjustments, and alignment with business goals—not instant success.

Evolving perspectives on AI

Initially, Afsheen viewed AI through a theoretical lens, focusing on technical breakthroughs and model optimization. Over time, her perspective has shifted to a practical approach that emphasizes seamless integration with business workflows for tangible value.

Now, she prioritizes building adaptable, scalable, and explainable systems that evolve with customer needs. AI isn’t solely about innovation at Motive; it’s about creating collaborative tools that drive long-term outcomes. This shift positions AI as a strategic asset, not just a technical solution.

How do we make our AI more accurate than others in the industry? 

At Motive, we ensure superior AI accuracy by using high-quality datasets and refining our models with real-world feedback. Our models undergo rigorous testing to handle edge cases and adapt to evolving customer needs.

This commitment to accuracy shapes Afsheen’s work, from thorough model validation to continuous improvement through feedback loops. She focuses on tailoring models to specific use cases, ensuring our AI consistently delivers accurate, reliable results.

Advice for evaluating AI solutions

When evaluating AI for productivity and safety, Afsheen says you should ensure the solution is tailored to your needs and scalable.

  • Prioritize explainability to understand decision-making.
  • Use high-quality, relevant data for accuracy.
  • Choose systems that support continuous improvement and can adapt to change.

At Motive, we’re enhancing predictive analytics to help businesses anticipate issues and improve AI explainability for decision-making transparency. These advancements build on our edge AI capabilities, keeping real-time, on-site decision-making at the forefront.

Why AI matters for enterprises

For larger businesses, AI optimizes fleet management and logistics at scale. It enables real-time decisions, predictive maintenance, and improved safety, ultimately reducing costs and enhancing productivity. AI’s scalability helps businesses grow while streamlining complex processes and enhancing productivity.

Looking to make an impact? Join our AI team at Motive- gomotive.com/careers