rtificial intelligence has revolutionised the way many businesses operate, providing tools and capabilities that enhance efficiency, drive innovation and improve customer experience. By automating tasks, providing deep insights through data analysis and enabling personalised interaction, AI helps businesses stay competitive and agile in a rapidly evolving market. Leadership now requires strategic management, ethical considerations and investment in human capital to fully realise AI’s potential and avoid the pitfalls.

Automation of routine tasks is the most immediate and visible effect. AI-driven automation reduces the need for human intervention in repetitive tasks, leading to increased efficiency and reduced operational costs. Chatbots and virtual assistants, powered by natural language processing, are revolutionising customer service by providing instant, round-the-clock support.

Customer centricity and engagement are crucial for the success of businesses in today’s competitive landscape. With the rise of digital platforms, customers have more choices, making it essential for businesses to engage customers to stand out from competitors.

Engaged customers are more likely to stay loyal to a brand and provide valuable feedback, helping businesses improve their products and services. Satisfied and engaged customers are also likely to become brand advocates.

Businesses can now tailor experiences and communications to individual preferences using data analytics and AI; engage customers through various channels like social media, email, mobile apps and in-person interactions; provide relevant, informative, and entertaining content; and offer rewards and incentives through loyalty programmes to encourage repeat business and long-term loyalty.

Customer data is the lifeblood of AI in business. It enables the development of intelligent systems that improve customer experience, drive operational efficiencies, enhance security and optimise marketing and sales efforts.

AI enhances decision-making processes through data analytics. Advanced algorithms can sift through vast amounts of data to identify patterns and trends that would be hard for humans to detect. This capability is invaluable for strategic planning, allowing businesses to make data-driven decisions with greater accuracy and confidence.

Predictive analytics, a subset of AI, helps companies anticipate market trends, customer behaviour and potential risks, enabling initiative-taking rather than reactive strategies.

Catering to specifics

Personalisation, driven by AI, allows businesses to tailor their offerings to individual preferences and behaviours. E-commerce giants like Amazon and Netflix use AI algorithms to recommend products and content based on user data, creating a highly personalised shopping and viewing experience. NLP and machine learning empower chat-bots and virtual agents to manage complex queries and learn from every interaction, continually improving the responses and effectiveness.

Driving innovation

The integration of AI into business is also a catalyst for innovation and the development of new business models, taking specifics to another level altogether. AI-driven insights can uncover unmet market needs, guiding the creation of new products and services. For instance, AI in healthcare is leading to the development of personalised medicine, where treatments are tailored to the genetic makeup of individual patients. In the financial sector, AI is enabling the creation of robo-advisors that provide personalised investment advice at a fraction of the cost of traditional advisors.

AI also facilitates the emergence of entirely new business models of the sharing economy, exemplified by companies like Uber and Airbnb. Here AI optimises resource allocation and improves user experiences. AI’s ability to analyse vast amounts of data in real time allows these platforms to efficiently match supply with demand, creating value for both providers and consumers.

Microsoft is deeply invested in AI, integrating it across its product portfolio to support various business needs. Azure AI is a comprehensive set of AI services and tools available on the Azure cloud platform, including machine learning.

Ethical considerations

The ethical implications of AI deployment are a primary concern. Issues such as data privacy, algorithmic bias and job displacement need to be addressed to ensure that AI benefits are shared broadly with robust ethical guidelines and transparent practices to mitigate any risks.

The data must be collected, stored and used in compliance with privacy regulations. Algorithmic bias must be avoided to maintain trust and prevent discrimination.

AI can render certain roles obsolete. Therefore, businesses must invest in re-skilling and up-skilling their workforce to prepare for an AI-driven future.

The road ahead

Leading the charge in this AI revolution are tech giants like SAP, Microsoft, Oracle and IBM. Their advanced AI tools are enabling businesses to streamline operations, enhance decision-making and drive innovation.

SAP integrates AI into its enterprise software to help businesses run more efficiently. SAP AI Core and SAP AI Foundation provide the infrastructure and tools necessary for developing and deploying AI applications. SAP S/4HANA incorporates AI and machine learning to automate routine tasks, optimise processes and provide real-time insights.

Meta’s advanced AI model, Meta Llama 3, known for its subtle understanding of language, will be utilised by SAP to generate scripts for highly customised analytics applications within SAP Analytics Cloud. SAP is also adding new large language models from Mistral AI, enhancing the generative AI hub capability within SAP AI Core.

Google Cloud’s Gemini models AI assistant and the Google Cloud Cortex Framework’s data foundation will integrate Joule and the SAP Integrated Business Planning for Supply Chain solution.

NVIDIA and SAP have introduced Joule versions specifically for consultants and developers. Joule’s role is to streamline data sorting and contextualisation, advancing automation and enhancing decision-making processes.

It is now embedded in SAP S/ 4HANA Cloud, SAP Build and SAP Integration Suite, delivering proactive and contextualised insights to business functions like human resource management, procurement, supply chain management and sales; soon coming for SAP Ariba and SAP Analytics Cloud, too.

Microsoft is deeply invested in AI, integrating it across its product portfolio to support various business needs. Azure AI is a comprehensive set of AI services and tools available on the Azure cloud platform, including machine learning, cognitive services, and bot services.

Dynamics 365 incorporates AI to provide insights and automate processes in areas such as sales, customer service and finance. Microsoft 365 uses AI to enhance productivity applications like Word, Excel and Outlook, offering features such as intelligent search, language translation and real-time collaboration. To enhance user experience, AI and machine learning enable Microsoft to aggregate meeting and call data across personal devices, Microsoft Teams meeting rooms, networks, IoT devices and Microsoft 365.

Oracle leverages AI to enhance its cloud and on-premises solutions, providing robust data management and analytics tools and embedding AI and machine learning capabilities across Oracle Cloud applications to automate tasks and improve decision-making.

Oracle Autonomous Database utilises machine learning to automate database management, ensuring high performance, security and efficiency. The AI-driven Oracle Digital Assistant helps businesses streamline interactions with customers and employees through natural language processing.

The writer is a freelance contributor. She writes about technology, education and social issues. She can be reached at hadiazaid2021@gmail.com