Published on October 29, 2023, 9:47 pm
The year 2020 to 2021 was characterized by disruption, and in response, many organizations pursued strategies of modernization. Digital initiatives focused on goals such as resilience, sustainability, and ROI as economies began to recover.
One technology that has gained significant sponsorship is artificial intelligence (AI). AI has shown great potential for accelerating digitalization and modernization efforts across various industries. James Ang, senior vice president for APAC with Dataiku, highlights six key areas where AI can drive organizational growth.
Firstly, AI enables productivity gains by optimizing business processes. Secondly, it augments the labor force by driving employee productivity. Thirdly, AI enhances customer demand through highly personalized products and services. The fourth area pertains to improving risk management—a matter of utmost interest to boards. Fifthly, AI can significantly enhance customer experience. Finally, AI plays a vital role in increasing market share for products and services.
Incorporating AI into business ecosystems presents its own set of challenges for leaders. According to Ang, the main challenge lies not in technology but rather in organizational culture and processes. Lack of culture from the top leads to failure in 95% of AI projects. To build an AI-powered organization successfully, a strong cultural foundation must be established alongside proper governance in three areas: AI governance, data governance, and explainability.
Skills and expertise are another challenge as there is a shortage of data scientists globally. Additionally, leaders often face the fear of the unknown when it comes to implementing AI strategies.
When developing an effective AI strategy, businesses should prioritize creating value for their organization. Dataiku advocates the 5 E’s strategy: explore what AI means for your business; experiment with early projects to estimate value; establish tangible value from initial use cases; expand the use cases across the organization; and embed the use of AI throughout all business activities.
To prevent failures during planning and execution stages of an AI strategy, clear goals, timelines, costs, leadership sponsors, and methodologies should be established. Quality data is crucial, as comprehensive, accurate, and unbiased datasets are necessary for success. Additionally, model explainability, continuous validation of models and algorithms, and compliance with data privacy regulations must be addressed.
To design an AI strategy that is not dependent on any specific vendor solution but instead dynamically aligned to the business, flexibility and scalability are key. A platform that accommodates large volumes of data and involves business users in a seamless manner can drive the organization’s success. When deciding between buying or building AI solutions, leaders should assess their organization’s core competencies and deploy resources accordingly while considering long-term planning and minimizing technical debt.
As technology continues to evolve rapidly, it is essential for organizations to future-proof their AI strategies by staying adaptable and agile. By embracing AI as part of their modernization journey, businesses can unlock significant potential for growth.
For further insights into regional AI development and discussions on these topics with James Ang from Dataiku, you can listen to the PodChat player provided in the source article.
In conclusion, adopting AI technologies effectively can accelerate digital transformation efforts strategically. Understanding the challenges associated with incorporating AI into business ecosystems and following best practices in AI strategy design ensures businesses are well-positioned for success in the modern world.