A Gartner survey revealed that 55% of organisations that have previously deployed AI always consider AI for every new use case that they are evaluating, while 52% report that risk factors are a critical consideration when evaluating new AI use cases.
What is AI in the enterprise?
Charlie Dai, VP and research director for Forrester, acknowledges that most leaders and users in APAC are aware of AI’s importance, and around 40% of decision-makers in the region believe that AI will improve their abilities to anticipate and respond to competitive/market changes, increasing automation of internal processes in the meantime.
Dai notes that the adoption of AI is still very nascent with 45% of firms in APAC expected to use AI infrastructure, while only 25% of them are expected to adopt AI/ML platforms.
Beyond Limits' president for Asia Pacific (APAC), Leonard Lee, says enterprise leaders in Asia understand that AI has the power to revolutionise business operations by automating routine and repetitive tasks, boosting efficiency, and reducing costs and time-to-market.
"AI could enhance the skills of existing talent and help business leaders fill the tech talent gap within the organisation, especially in process-driven industries such as manufacturing," he added.
"By integrating human expertise and knowledge with AI solutions, workers will work more efficiently, and enterprises will be better equipped to make strategic decisions to achieve their business goals."
Leonard Lee
The key to improving the value delivery of AI in the enterprise may lie in putting AI where there is a lot of information and analytics needed in one place.
"Each organisation in each industry needs to evaluate where this starting point is; cognisant of the fact that on an enterprise or corporate level, AI can be most helpful in assisting with repetitive or data-heavy tasks that are not the best use of a human resource," said Gibu Mathew, VP and GM APAC at Zoho.
Sandie Overtveld, senior vice-president for APJ & MEA at Freshworks warns that with AI needing an abundance of data, it is crucial to also consider security and maintenance on the cloud as well as ownership of data.
A measure of success – scaling
Robotic process automation (RPA) grew in popularity largely on the promise of automating boring processes, which also included minimising errors arising from repetitive, monotonous processes. However, one early observation is that organisations found it challenging to scale RPA deployment after the first few applications.
Given that a business is comprised of multiple functions that operate independently of each other but share a common business objective (drive customer value, generate revenue, grow), what can enterprises do to scale AI across the rest of the organisation?
Lee suggests clearly defining the goals shared by the entire organisation and outlining how they can be measured must be the guiding principle for scaling initiatives.
"AI solutions serve as a bridge between both and align departmental objectives with the overall organisational goals. Creating a shared and centralised infrastructure—which should be inherently enabled by AI—to promote collaboration and knowledge sharing must then be established," he explained further.
Mathew believes that collaboration is fundamental, and the right tool or platform is critical to that. Secondly, he adds, it must be friendly both to IT and business users.
Though both are critical to the business, their tendency to have opposing priorities can be a major pitfall when trying to scale AI enterprise-wide," he added.
"Simply, any AI-powered platform or tool must offer business users the flexibility to work independently without requiring constant IT or engineering support. Meanwhile, IT needs a platform that will ensure adequate constraints that adhere to predefined and IT-approved paths."
Gibu Mathew
Freshworks' Overtveld opines that the scalability of AI on an organisational scale is made possible by an omnichannel approach that creates a degree of unification of customer data from across a company's various methods of communication.
"Customer-facing teams require in-depth information and context for better service," he added. "With an omnichannel approach, businesses can unify and personalise customer conversations across multiple channels of communication."
Forrester's Dai raises the existence of a trust gap between AI and impact. "To strengthen the AI business case, firms must quantify and communicate uncertainty; and ensure consistency with ModelOps to detect and mitigate performance issues.
"Leaders should showcase dependability through simulation; embrace transparency with traceability; hire a chief ethics officer or chief trust officer to ensure integrity; and imbue AI systems with empathy through stakeholder feedback."
Charlie Dai
The value proposition of AI to the enterprise
Beyond Limits' Lee cautions that decision-makers must recognise that AI is not a one-time magic wand but part of a continual improvement process.
Dai says foundation models will play a key role, but business knowledge and data management will also be critical to unleash the true power.
Lee suggests AI engineers continually work with subject matter experts and learn about their respective domains, through studying their work from an algorithm and process perspective." He posits this will ensure that their expertise is encoded into a knowledge base that is constantly updated, enabling the Cognitive AI system to keep its recommendations and explanations accurate and understandable."
Overtveld believes that the next step in the evolution of AI would be in accessibility and personalisation.
"While the opportunities to streamline and enhance operational efficiency are paramount, it is as paramount to include both employees and customers in the process.".
Sandie Overtveld
"This necessitates the integration of Generative AI in software utilised to consider the needs, concerns and experiences of both employees and customers alike," he concluded.
Acknowledging AI's growing popularity in the enterprise, Zoho's Mathew warns that it is not enough to follow the herd; each organisation will have their own needs. By fostering a culture of innovation and continuous learning, businesses can unlock the true potential of AI and leverage its transformative possibilities.
