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The role AI is playing in boosting economic development in emerging markets

The role AI is playing in boosting economic development in emerging markets

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The need for organisations to make quick decisions from huge volumes of data has made Artificial Intelligence (AI) one of the key focus areas for technology investment over the last two years. But AI’s rapid rise to prominence has left some organisations in the Middle East and Africa (MEA) struggling to build the capabilities required to implement it successfully and realise its full potential of boosting economic development.

Andrea Tucker, Head of R&D, e4.

Artificial Intelligence (AI) has enormous potential to augment human intelligence and to radically alter how we access products and services, gather information, make products, and interact. In emerging markets, AI offers an opportunity to lower costs and barriers to entry for businesses and deliver innovative business

models that can leapfrog traditional solutions and reach the underserved. With technology-based solutions increasingly important to economic development

in many nations, the goals of ending poverty and boosting shared prosperity may become dependent on harnessing the power of AI. While emerging markets are already using basic AI technologies to solve critical development challenges, much more can be done, and private sector solutions will be critical to scaling new business models, developing new ways of delivering services, and increasing local markets’ competitiveness. All of these solutions require innovative approaches to expand opportunities and mitigate risks associated

with this new technology.

Hriday Ravindranath, Managing Director, Global Portfolio, Digital and AMEA, BT, said AI – the simulation of human intelligence by machines – is going beyond automation, where a machine is programmed to complete a specific task, to now include learning from experiences, reasoning and self-correction. Ravindranath said this is leading to augmented intelligence, where technology is supporting and enhancing the human understanding.

While globally there is an immersive mindset change to AI emerging, many business leaders across the Middle East and Africa (MEA) remain sceptical, citing concerns around the potential negative impact on jobs.

Rudie Opperman, Manager Engineering and Training, Middle East and Africa – Axis Communications, said the optimism around AI is widely spoken of and almost becoming a household name in so many industries. “Most people will easily gravitate towards the promises it brings and the improvements it could potentially deliver. From our perspective in the realm of security and IoT, we cannot deny that the potential benefits are real and promising,” he said.

According to Opperman, CIOs in the Middle East and Africa (MEA) can improve their positioning with AI by starting to build trust and aligning with suppliers and manufacturers who have clearly demonstrated their commitment to a smarter and safer world. “Other important topics like sustainability and cyber security needs to be roped into these AI discussions and the potential risks also need to be weighed against the potential benefits,” he said.

Stephen Gill, Academic Head of the School of Mathematical and Computer Sciences, Heriot-Watt University Dubai.

At Heriot-Watt University Dubai, Stephen Gill, Academic Head of the School of Mathematical and Computer Sciences, said it is no secret that the massive digitalisation shift accelerated by COVID-19 has presented unprecedented challenges to CIOs. Gill said faced with an unpredictable market and new variables, reference to historical data proved futile. “With business priorities significantly shifting and employees’ tasks changing accordingly, driving automation, among other technological adjustments, has proved to be the way forward. “To succeed in this new business climate, CIOs must create new business models that can get their organisations up to speed with market conditions. Fortunately, AI is capable of utilising real-time data to build solutions suitable to the current business climate,” he said. “New business models are undoubtedly required to bridge the gap between market conditions and company operations. It has been proven that cost/benefit forecasting based on historical data can no longer be a reliable indicator in unpredictable market conditions and changing customer needs.”

Gill said in this situation, adopting an AI-approach can help CIOs build data-centred strategies based on a real-time understanding of their customers and the market. “This has proven to help business adaptability in times of changing habits and preferences. For example, within e-commerce and retail, AI and Machine Learning technologies are extensively used to recommend products to customers, forecast future demand for products and other functions,” he said. “This is the case with Amazon where AI use is deployed to enhance consumer experiences through analysing their shopping patterns to recommend products accordingly. This undoubtedly increases the chances for customer loyalty and retainment.”

With some AI projects failing to yield the desired outcomes for organisations, CIOs and IT teams have been cautioned to clearly define their AI goals before implementing

Andrea Tucker, Head of R&D at e4, said the biggest areas to be aware of for CIOs is to ensure they have the problem statements clearly thought through and documented. “And document what success looks like. Make sure that you can quantify the benefits of a successful AI integration. You can’t assess a pilot successfully if you haven’t got these things documented,” Tucker cautioned. “Listing criteria for success upfront makes the decision to proceed or not easier. These need to be meaningful to measure in business terms and they should explicitly link to the outputs of the AI work to be meaningful and measurable. If black and white metrics aren’t easy to ascertain, decide what level of improvement to expect in the business measure as a result of the AI work.”

Julia Carvalho, General Manager, IBM Africa Growth Markets.

Julia Carvalho, General Manager, IBM Africa Growth Markets, said it is important for organisations to continue to re-examine their strategies and tools that will set them apart. Innovation often creates superior long-term benefits and practices. Carvalho said the digital revolution induced by the pandemic has led new norms and organisations must be increasingly aware that the new ways of interacting with their ecosystem is only going to intensify. “Organisations must embrace AI and this starts with thinking critically about the problems the business is facing, framing those challenges in ways that are potentially solvable by AI, and then identifying and refining use cases that are critical to the business goals,” she said. “This way, CIOs will design AI that successfully connects every strategic data and to the defined business objectives of a company. Once the intent of AI in the organisation is set, leaders should then define the types of AI solutions needed by the users and that will eventually be integrated into your infrastructure. AI is rapidly advancing in numerous fields, from computer vision that determines what’s in an image to the natural language processing AI that you find in chatbots and virtual assistants. What are the ways these applications can advance the intentions you outlined?”

Carvalho said the next question for CIOs will then be to figure out what data they need to make the use cases identified effective and that their AI is being fed accurate, clean data that draws from the entire organisation. “This will need to be followed by setting concrete actions in place for the technical implementation. This will ensure AI is operationalised through the business by connecting every solution to the defined AI strategy,” she said.

Ravi, Co-founder and President, Uniphore APAC, said: “In recent years, AI has rapidly evolved from a fringe technology, to now being a crucial component in the Digital Transformation and innovation strategies of businesses. This change requires organisations to adopt a more comprehensive, long-term outlook for AI-adoption which inevitably calls for the incorporation of an overarching AI architecture. Such a robust architecture will allow the seamless integration of AI with other advanced solutions like natural language processing (NLP), automation, machine learning (ML), and more – allowing for holistic value creation across a multitude of use cases.”

Saraogi pointed out that customer service stands out as an especially relevant area of application and could serve as an ‘easy win’ for MEA organisations looking to make their first foray into AI. “By optimising conversations between people and automated systems, AI has augmented – not replaced – human capabilities to enhance the way businesses interact with their customers. After achieving this first milestone, MEA organisations can look to unleash AI’s true value for enriching customer experience and enhancing conversations, by exploring how this technology can be infused into existing business systems to build a multi-layered AI architecture of the future,” Saraogi said.

According to Carvalho, organisations must ensure that AI systems operate within a basic ethical framework and AI machines are embedded with values. “They must begin by creating a set of rules with which the system must comply and then – over time – identify subtler, ethically ambiguous situations, accepting training and direction on how to handle those situations going forward,” she explained. “Bad algorithms will yield bad results. While investment and experimentation are extremely important, the biggest and most common strategic mistake companies make when exploring AI is failing to define a clear use case and desired outcomes with a clear, quantifiable metric for the technology in the first place.”

She explained that CIOs need to start with a clear understanding on who will be consuming the AI solution, how they will be consuming it, and why AI is even needed. “This starts with thinking critically about the problems the organisation is facing, framing those challenges in ways that are potentially solvable by AI, and then identifying and refining use cases that are critical to the business goals,” she said. “Without this approach they risk issues such as training a Machine Learning model using data that contains human bias or suggests humans make unfair decisions. The reality is that by putting trust at the cornerstone of AI innovation, business leaders have a major opportunity to use AI as a force for positive change, both for their companies and for society at large.

Given that there are many technologies and disciplines that involve Artificial Intelligence, Tucker believes voice, visual, text recognition and incorporating services that automatically recognise speech must be part of the AI solution.

Tucker said without a doubt, AI will become more strategically significant with a focus on long-term scalability in the next five years for large organisations.

“But for end consumers like us, we can anticipate ‘Alexa’ and other similar home pods to travel with us. Alexa won’t just be turning your specific playlist on while you cook dinner, but she’ll be with you permanently: monitoring how your body is functioning and make suggestions on how to be healthier, she’ll be reading all your correspondence and writing your to-do lists, solve potential problems for you, submit your online shopping orders and pick the best delivery time. She may even be able to read our thoughts – what that looks like is almost inconceivable right now, but I’m sure it’s coming.”

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