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Artificial intelligence top priority for organisations, but challenges remain

By Shannon Williams
Mon 3 May 2021
FYI, this story is more than a year old

Organisations across the Asia Pacific region are leading the charge toward artificial intelligence adoption, according to new research from Juniper Networks. 

The company found both consumers and enterprises want to use AI to a greater extent – and many executives have put it as a top strategic priority for 2021. However, challenges still remain that have hindered actual adoption. 

Juniper conducted the global survey of 700 IT decision makers with direct involvement in their organisation’s AI and/or machine learning plans or actual deployments to assess the attitudes, perceptions and concerns of the technology.

The study highlighted that respondents in the Asia Pacific region displayed greater levels of trust toward AI, with a higher degree of confidence that AI will play a bigger role in their lives going forward than their counterparts in North America or Europe. 

A key research finding was that some 99% of APAC respondents feel their organisation would benefit from the embedding of AI into their daily operations, products and services. In fact, some 42% of respondents reported that 50% or more of their operational decisions are currently assisted by AI decisioning, or will be soon, compared with only 23% of respondents in North America.

 Customer Service is reported as the most common business area currently utilising AI. This has helped to drive broader acceptance and trust, while also accelerating AI adoption and fuelling the demand for employees who are skilled in AI development. With digital technology tangibly benefiting the way enterprises and individuals operate in the region, respondents in Asia (71%) are more open to seeing AI as their co-worker of the future than in North America (54%).

While the adoption and development of AI in the Asia Pacific region is growing rapidly, Juniper’s research show that respondents are looking to overcome challenges, primarily in the following areas:

  • AI-Ready Technology Stacks: Respondents ranked developing AI models and data sets that can be used across the company as the top technology-related challenge. There is a need for stronger infrastructure – including data, cloud and networking capabilities – and talent to work with AI systems, as more than half of executives (74%) are likely to collect telemetry data to enhance AI to improve user experience.
  • Workforce Readiness: 48% of APAC respondents’ organisations are struggling with preparing and expanding their workforce to integrate with AI systems. Providing tools and opportunities that help employees apply AI skills is a top priority for leaders, while developing plans and metrics to expand employee skillsets and recruiting pipeline are also of importance. Meanwhile, C-level respondents reported they feel it is more of a priority to hire people to develop AI capabilities within an organisation (Priority No. 1) than it is to train end users to operate the tools themselves (Priority No. 2). 
  • AI Governance: 75% of APAC respondents reported that AI has been identified as a priority by their organisation’s leadership team for their FY21 strategic plan and 87% of executives agree cross-functional executive sponsorship and involvement is critical for AI to integrate into their products and services. Despite broad acknowledgement from respondents, only 3% of executives reported that they have identified a company-wide AI leader who oversees AI strategy and governance.
     

Although AI does come with its own set of challenges, Juniper’s research shows that organisations that have already adopted and harnessed the power of AI are showing real and meaningful outcomes.

The survey revealed Sales and Marketing, as well as Finance and Accounting, are the most common business areas where organisations are currently utilising AI, with positive changes like operational efficiencies and enhanced user experience being seen. 

The research also shows that as organisations scale their AI capabilities and integrate their employees into their solutions, user satisfaction steadily rose and the time given back allows employees to focus on value-add tasks they could not previously accomplish.

“As a CIO, when I see so much interest in an emerging technology, I always need to remind people there are pitfalls if it’s not managed correctly," says Sharon Mandell, SVP and CIO, Juniper Networks.

"For artificial intelligence, there is no doubt that there is light at the end of the challenge-filled tunnel, and significant potential to generate even more meaningful and incredible outcomes than we have seen so far. 

"By focusing on upskilling their workforce, investing in strong infrastructure – including data, cloud and networking capabilities – and implementing enterprise-wide AI governance, organisations are preparing for the digital workforce of tomorrow," Mandell says.

“From chatbots in customer service, to discovering new areas of operational efficiencies, and intelligent networking solutions that facilitate seamless transition between devices, these use cases define what it means to work in an experience-first era," she explains.

Mandell says that as the integration of AI technologies continues to deepen in the modern workplace, organisations in Asia Pacific need to have the right mix of talent, AI-driven technology and IT governance. 

"This will provide business leaders with the foundation to build an agile, digital-centric workforce who are ready to embrace change and deliver exceptional experiences for their business, customers and communities.”

Ang Thiam Guan, VP & GM, APAC, Juniper Networks, adds, "At Juniper, our mission is to leverage AI to simplify operations and deliver superior experiences for enterprisers, service providers and cloud providers.

"From wired and wireless access and SD-WAN, to campus and data centers and multicloud environments.

"Juniper’s AI-Driven Enterprise portfolio brings unprecedented simplicity, reliability, and security to enterprise networks. Automated network monitoring, management and troubleshooting from client-to-cloud provides better insight so that operators can focus on higher level tasks and end users can focus on consuming value – without the need to hire outside people with AI expertise. "  
 

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