By David Irecki
You might not think of it often, but you’re using artificial intelligence in your everyday consumer life.
AI is at work personalizing your social media feeds and your online shopping experiences. If you map a weekend getaway, AI helps figure out the fastest route based on real-time traffic data. Your email inbox is mostly free of spam because AI shoos spam into its own folder.
These consumer conveniences dwarf what AI is poised to deliver in your professional life, whether you’re on the business or IT side of your organization. AI is about to disrupt and reshape business as we know it.
The AI revolution will be especially pronounced in Asia-Pacific, which several research studies predict will be the fastest-growing market for AI among all global regions. For instance, a study by Allied Market Research foresees a 41.0% compound annual growth rate (CAGR) in Asia-Pacific through 2030, higher than a 38% CAGR globally.
“Asia-Pacific is expected to witness significant growth during the forecast period, owing to economic and technological developments in the region, which [are] expected to fuel the growth of artificial intelligence solutions in the region in the coming few years,” Allied’s report says.
A Majority of Enterprises Will Use AI in Asia-Pacific
Adoption across Asia-Pacific will see a majority of enterprises embed and infuse AI across business and IT, while looking to boost AI skills among IT pros and taking advantage of low-code development, according to IDC, a leading global consultancy.
In a recent report, IDC predicts that:
- About 65% of Asia-Pacific organizations will embed AI across business technology categories by 2026, using AI to improve outcomes without reliance on technical talent.
- About 75% of large Asia-Pacific organizations will use AI-infused processes to boost asset efficiency, streamline supply chains, and improve product quality by 2026.
- A talent gap will drive 55% of IT organizations to invest in AI skills by 2023 to automate IT operations and support business users.
- Most organizations in Asia-Pacific will use low-code/no-code development tools for 30% or more of AI and automation initiatives.
But it’s not as simple as flipping a switch. IDC advises that to capitalize on AI’s promise, Asia-Pacific organizations need to craft a strategic roadmap that addresses the underlying data infrastructure and prioritizes business use cases.
“Changing market dynamics are pushing APAC organizations to take a disciplined approach to scale AI initiatives and generate improved business impact,” IDC’s report says. “For AI to reach its full potential throughout the region, sharper business use cases and a more robust data ecosystem are required.”
Pitfalls and Challenges on the AI Journey
As a global leader in intelligent integration and automation, Boomi has continually incorporated AI into our technology. A dozen years ago, we introduced Boomi Suggest, which uses machine learning (ML) to suggest integrations based on anonymized metadata of customers that have done the same integrations.
As we roll out Boomi AI, a first-of-its-kind tool that uses generative AI to integrate applications, data, processes, people, and devices, we’re finding a great deal of interest among Asia-Pacific customers in how AI can help them advance to a next level of business speed and precision.
But our customers are also well aware of challenges and potential pitfalls of an AI journey. Warnings of AI dangers from top AI experts have received high-profile media coverage around the world, with scenarios ranging from “deepfake” images and videos that undermine public trust to an AI-ruled dystopia that leads to human extinction.
Governments are responding. Countries across Asia Pacific have been bringing together groups and proposing measures to govern generative AI services and guide the development of generative AI. In late May, Australia’s industry and science minister released a paper proposing regulations for the sake of safe and responsible use of AI within the country. Meanwhile, Singapore has unveiled a national AI strategy, and the recently-formed AI Verify Foundation will look to the open source community to develop AI testing and tools to assure the responsible use of AI.
AI Demands a Robust Data Ecosystem
While business concerns around AI differ from a government’s, it’s critical that your organization pursues AI with an emphasis on the “more robust data ecosystem” that IDC called out in its report. Areas to cover in your AI strategy should include:
Data accuracy. The old saying, “garbage in, garbage out,” is especially true with artificial intelligence. AI is only as good as the data at its disposal.
It is imperative to ensure that data supplied to AI for analytics is accurate. That’s achievable with technology that can aggregate data from disparate source into a single source of truth. The right approach will resolve discrepancies, standardize data definitions, and provide an ongoing assurance of high data quality.
Data completeness. It’s also important to determine whether your data sets are sufficiently complete. Data sample sizes that date back only six months can generate less accurate AI output versus data sets covering three years. That poses a risk if you’re using AI for predictive analytics to size up issues such as customer churn or profitability by product.
Process integrity. Similarly, your process workflows need to be logical and seamless if you’re looking to AI for automation. AI may be able to suggest optimal workflows, but it’s up to you to test sequences and try to “break” a workflow with an unexpected condition. Due diligence up front will minimize risk of a process disruption that leaves stakeholders stranded.
Trust and security. Securing sensitive data, including personally identifiable information (PII), is vital to building trust among stakeholders, both internal and external — especially your customers. Look to ensure data access only to authorized systems and individuals, and implement a data governance framework that strengthens accountability and compliance with company and regulatory standards.
An Intelligent Strategy To Capitalize on AI
Establishing a robust data ecosystem at the start will equip your organization to reap the rewards of artificial intelligence in the near term and for years to come. Done right, an intelligent approach to AI can help your organization:
- Improve cost efficiency by automating manual processes
- Enhance customer experiences, from onboarding to support
- Optimize supply chain lifecycles, from sourcing to distribution
- Generate breakthrough insights via AI analytics
- Accelerate and refine product and service development
- Liberate staff to focus on value-add initiatives, not spreadsheets
Stay tuned for the second in this two-part blog series, in which we will examine how Boomi’s AI capabilities can help you create an intelligent integration and automation ecosystem that lets you take full advantage of your data — and of AI’s promise.
Learn more about Boomi’s position on AI in our executive brief, “Why an AI-First Strategy Is Essential for Success.“