How Generative AI reinvents the way we work

After capturing the public’s imagination in 2022, generative Artificial Intelligence (gen AI) began to permeate the business landscape in 2023. 2024 remains a crucial year for the future of AI, with researchers and organisations pushing the boundaries by developing new algorithms and models to tackle increasingly complex tasks.

A recent IBM report found that three out of four (75%) global CEOs believe that the organisation with the most advanced gen AI will have the ultimate advantage. Moreover, 43% of CEOs said they will use gen AI to inform strategic decisions. Companies worldwide are recognising the benefits of gen AI and its crucial role in their success. This is driving a new era of work, productivity and opportunities across industries. AI is projected to enhance human productivity and unlock an astounding $16-trillion in value by 2030. In perspective, the fifth largest economy by gross domestic product (GDP) in 2023 was about $3.7-trillion. When combined with automation technology, gen AI can help clients improve interactions with customers and partners, as well as boost operational efficiency and productivity. 

Slow but steady AI adoption in Africa

This is not just a global phenomenon; half of the African CEOs surveyed in our IBM report expect to realise significant value from advanced AI and analytics. However, adopting AI is not without its obstacles. Many businesses on the continent and beyond are grappling with a multitude of challenges. Globally, 82% of IT professionals say IT complexity is impeding success in deploying AI, while 55% of business leaders lack key information regarding their technology spending decisions. In Africa, many organisations face barriers such as costs, market and regulatory factors, workforce readiness, infrastructure, skills gap, ethics and governance.

_{Saad Toma, General Manager, IBM Middle East & Africa}

Become an AI-first organisation to stay ahead

To overcome these challenges, organisations must move to an AI-first approach, where AI is integrated into their business strategy across the lifecycle. Being AI-first enables businesses to be value-creators rather than solely value users. Companies that will lead their respective industries for the next decade or two will be the ones that decide to be AI-first. That is why we launched watsonx in 2023 to develop trusted AI and drive innovation for organisations in every sector or industry. Building an open-source AI community is a core part of our AI strategy. At our recent THINK conference, we further enhanced watsonx’s data and automation capabilities to make it more open, cost-effective, and flexible for businesses.  We achieved this by releasing a family of IBM Granite code models to the open-source community. We launched InstructLab with Red Hat, to enhance large language models and open the doors for those with minimal machine learning experience to contribute. We also announced IBM Concert that uses AI-powered automation to help businesses to discover gaps, prioritise insights, reduce complexity and streamline operations for more innovation and cost-effectiveness.

Putting IBM AI solutions and watsonx to work across industries

Since the launch of watsonx, we have over 700 client pilots running and managing over 1,200 AI models globally. We have also increased the accessibility of watsonx by making it available on AWS Marketplace, reaching 92 countries worldwide, including 18 in Africa. To name a few examples, we are leveraging watsonx’s geospatial foundation model built from NASA’s satellite data to ensure climate resilience with the Government of Kenya. watsonx is enabling local scientists to track and visualise tree-planting activities to assist the government’s goal of planting 15-billion trees by 2032. Working with Neostream Technology, an IBM business partner based in Kenya, we successfully deployed and integrated IBM Instana with M-GAS – a premium provider of liquefied petroleum gas in the country. The deployment of Instana has provided real-time monitoring and visibility. This has empowered M-GAS to track critical business applications with granular application-level insights. This has empowered M-GAS to address issues across all layers of their technology stack that previously could not be delivered by traditional monitoring tools. Lastly, Instana’s intuitive interfaces and customizable dashboards have offered rapid issue identification and resolution, fostering team collaboration, minimising downtime, and enabling M-GAS to intervene proactively to ensure uninterrupted gas supply to their customers.

In the Middle East, we partnered with the Saudi Data and Artificial Intelligence Authority to launch an open-source Arabic Large Language Model, ALLaM on watsonx.  This has enabled the deployment of Arabic gen AI models, which opens the possibility of building AI models for Africa using the continent’s rich and diverse languages. Globally, working with Transport for London, we deployed IBM Maximo to assist in managing the day-to-day maintenance efforts for more than 10,000 internal technicians within the London Underground. Above ground, the software enables the tracking, support and oversight of numerous contractors – helping extend existing equipment’s life and keeping commuters happy.

Across the world, organisations are leveraging IBM’s AI business solutions to solve business challenges. Their use cases range from banking and financial services, energy, telecommunications, climate change and sustainability, customer services and entertainment to name a few.

The right partnerships and governance are key

The adoption of gen AI is accelerating across enterprises as organisations aim to gain a competitive edge and unlock new opportunities. To achieve this, organisations need to have a robust AI strategy and the right level of investment. They also need to establish and implement clear and consistent standards or guardrails concerning the utilisation of AI across all strategic focus areas. Most importantly, they need the right partner who understands the overall business objective and how to overcome barriers preventing AI adoption. Such collaborative partnerships are critical for developing robust data and AI strategies, filling the skills gaps, and guiding the organisational change necessary for successful AI adoption.