Everyday Reflections

Gen AI is popular for boosting productivity, but it can also be a catalyst for progress in emerging economies. Despite accounting for 85% of the world’s population, the challenges faced by countries in the Global South are often overlooked. 

Here are just a few use cases of AI tools: 

• Enable patients in remote areas to access healthcare in a local language.
• Help fishermen get life-saving weather alerts.
• Offer students personalised tutoring that factors in limited connectivity.
• Empower livelihoods as farmers can monitor crops in real-time.

But scaling AI products to ensure adoption and alignment with the needs of underserved markets presents challenges: 

• Inadequate infrastructure due to a lack of investment remains a key hurdle to AI adoption in EMs, according to a G42 and Economist Impact report. Political and economic factors, including currency volatility, regulatory and political instability, have restricted large-scale investment in many markets, it said. Talent flight is also common as engineers move for better pay to developed countries.

• Fast internet remains an urban privilege as rural India lags, and there’s exclusion from the digital ecosystem. Around 91.6% urban households report having internet access, while the figure falls to 83.3% in rural areas, as per NSS data. 

• India has 22 official languages and hundreds of dialects. Yet, LLMs focus on global languages. Understanding linguistic context can be a challenge for AI and requires localisation.

Leaders and policymakers need to scale AI ventures without sacrificing ethical governance, build trust in the product, and make services inclusive and affordable. Philanthropic capital and public-private partnerships can help bring in funds. 

Taking a Product Nation approach to build an AI product roadmap can chart progress, communicate with stakeholders, and give an overview of milestones. Feedback loops and iteration can be done to improve the product.​ The policy framework, coupled with sustainable development and with inclusive culture, is the key to increasing penetration. Above all, product management in the current era would be challenged on how to lower the barrier of cost to make the tech reach the masses. 

We need to view metrics beyond output/growth, focusing on indicators to analyse user satisfaction and engagement. The products must be usable and tailormade to fulfil people’s needs.

Human-in-the-loop (or HITL) principle will be critical as we harness automation provided by AI and complement it with human decision-making. Cross-disciplinary teams will be needed, which allow for collaboration and incorporate product management functions along with data science skills, knowledge of ethics, and operational efficiency. 

The potential of AI to reshape emerging markets is vast and untapped. It’s a long journey, but the way to get there is by focusing on promising ideas, incentivising the workforce, understanding user needs, experimentation and iteration.  

#ProductManagement #AI #ArtificialIntelligence #GlobalSouth #DevelopingCountries