See Your World Clearer
AI improves decision-making for people.
AI models are computer tools that helps us to see the world clearer and faster, in ways we never could before such that now, we can solve important problems like use mobile phones to dramatically reduce waste from farms, help doctors and pharmacists diagnose more patients and automate repetitive tasks.
AI is a necessary competitive advantage for any business or innovative endeavor that will survive this coming decade.
Industry scenarios in Africa
AI is a broad-stroke tool that can process a large pool of data to recognize patterns, contextualize what they mean and where appropriate, predict future events.
The top 3 industries we see AI driving tremendous value in Africa are profiled below.
Healthcare
Diagnose disease in rural areas;
Study African genes to cure serious conditions like cancer
Agriculture
Predict Bad Weather
Detect Pest and Diseases
Count Produce on Large Farm
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Manage Customers
Richer customer insights and tailored experiences
Manage Operations
Optimized production, logistics and maintenance
Manage Administrative Functions
Faster, better, cheaper administrative processes
Manage Enterprise & External Risk
Intelligent risk detection, prediction and prevention
AI By Datatype
Given thousands of images, AI models can be trained to recognize the contents of the images or videos and spot patterns. Common use cases are to take pictures with drones to identify pests in large farms, cameras in stores to understand customer behavior or MRI machines to spot cancer cells in people
With AI, it is possible to capture sound data for analysis to recognize and understand patterns, which might lead to making correct business decisions that previously eluded us. For example, there are companies listening to the cries of babies and diagnosing particular respiratory diseases. Others are experimenting with listening to the engines of cars and detecting mechanical issues.
AI is able to process large volumes of text and even sound data to understand the underlying language being communicated, which in-turn is used to solve desired business problems. In this domain, we have seen companies build chat-bots to improve customer care, translation tools for events, models to understand client behavior in-order to provide tailored services and email readers to process large volumes of content quickly.
Your Tough Questions
As you start to think-through these questions, contact us at Alliance for AI to connect you with answers that work for you
- Is machine learning applicable to my business or situation?
- How and where do I start an AI initiative within my company?
- What new technology is needed to put AI to work in my company?
- How will AI work seamlessly with existing data/ systems?
- How long will an AI initiative take from planning to execution?
- What data (and how much data) will I need to collect?
- How should I ingest, store, label and represent data?
- Which modeling approach/ algorithm should I use?
- How do I identify the right set of partners and open source tools?
- How do I evaluate the performance of my ML algorithms?
- When do I know that the model is trained enough, or accurate enough?
- How do I consume new data sources and scale for enterprise-wide use?
- How do I explain and justify the model’s decisions?
- How should we organize, recruit, measure, reskill and reward AI teams?
- Which business function should have primary ownership of AI efforts
- What happens after I launch my ML product or service in the market?
- What new risks could I face and how can I mitigate them?
- How do I plan for disaster recovery, data breaches and threats?
- How should I address concerns such as job displacement?
- What societal, ethical, privacy and regulatory considerations exist today?