Covering Disruptive Technology Powering Business in The Digital Age

Written By: Philip Madgwick, Senior Director, Asia, Alteryx

Artificial intelligence (AI) is fast becoming a strategic imperative for many businesses, providing a whole new business opportunity for delivering decision intelligence at scale. Yet, AI continues to be shrouded in mystery, uncertainty, and apprehension. Many industry experts are coming forward to warn against the aggressive campaign undertaken by companies to create AI products. Concurrently, fears of job security due to AI have been growing among workers, with 6 in 10 Singaporeans fearing that AI will replace their jobs, according to Microsoft’s 2023 Work Trend Index.

As the capabilities of AI rapidly expand to deliver countless AI-driven business opportunities, many enterprises find themselves grappling with the complexities and implications surrounding its adoption. Ultimately, any technology is only as effective—or as impactful—as the person using it. So, how can businesses untangle the myths and confusion around AI to address concerns and approach adoption holistically?

Illuminating the Other Side of AI through Practical Applications

While news headlines these days are dominated by generative AI, it is essential to recognise that the applications of AI within the enterprise extend far beyond these buzzworthy examples. The explosion of data and falling cost of computing power have created fertile ground for AI and machine learning, with AI revolutionising the fields of retail, finance, healthcare, and manufacturing.

AI-powered analytic automation tools have played a crucial role in driving productivity, efficiency, and innovation for businesses. Specifically, the rise of self-service analytics tools with easy-to-use and intuitive interfaces has empowered non-traditional data scientist employees to harness the power of data by democratising AI expertise and simplifying AI concepts.

In an environment fraught with high inflation, economic uncertainty and a tightening labour force, organisations have been turning to enterprise AI to unlock opportunities, deliver insights at unimaginable speeds, and make strategic decisions. When leveraged properly, AI, specifically generative AI, allows knowledge workers to replace the daily time spent on manual time-heavy tasks to focus on the highest-value portions of their jobs, as well as provide new pathways to decisions intelligence and insights.  With the rise of user-friendly AI platforms, the use of AI grows increasingly accessible to both technical and non-technical users, creating new pathways to decision intelligence and insights.

Unravelling the Confusion around AI

As more businesses look to integrate AI tools into workplaces, there are three areas leaders can consider: creating transparent and explainable processes for generating AI-powered insights, establishing clear governance, and building trust within the workforce.  As with any emerging technology, thoughtful leaders must take a pragmatic approach to how AI can aid their people while ensuring they have effective guardrails to protect them. It is imperative that the processes that generate AI-driven insights are auditable, explainable, and reproducible.

“Artificial intelligence (AI) is fast becoming a strategic imperative for many businesses, providing a whole new business opportunity for delivering decision intelligence at scale. Yet, AI continues to be shrouded in mystery, uncertainty, and apprehension.”

Without the right cross-departmental skillsets, data knowledge, and governance factors, the data selected to feed AI models can be flawed, incomplete, or non-compliant. There are over 20 mathematical definitions of fairness from a firm’s standpoint —which one the company should use is a business decision that should not be left solely to the developer. Without knowing what went into the model or how the model works, users may have difficulty fully understanding the appropriate use for the responses. When the input is made explainable, it becomes clearer how large language models and AI fit within the business, making it easier to trust the outputs.

Building AI Trust in the Workforce

Despite the heightened promise of AI,  only 53% of AI projects ever make it from prototype to production, according to Gartner. Deploying AI—or any IT solution—without consideration for change management can result in failed adoption and wasted budget. Business leaders must bring their employees along on the AI journey to succeed here. The absence of clear data governance, technology policy and communication processes within an organisation also leads to low trust and confidence in adopting new practices and solutions.

Recognising the need for transparent and trustworthy AI practices, Singapore’s Infocomm Media Development Authority (IMDA) and Personal Data Protection Commission (PDPC) launched the world’s first AI governance testing framework and toolkit, A.I. Verify, to promote transparency through process checks to foster public trust’s in AI.

Responsible AI Use

Organisations can learn from such frameworks and adapt them to their internal governance processes, ensuring responsible and accountable AI usage. Building trust in AI can also be achieved in several ways, including inviting safety and trust experts to discuss implementation, launching pilot programmes to familiarise the workforce with the tools, and opening channels of communication to leadership teams to convey issues or concerns.

“As more businesses look to integrate AI tools into workplaces, there are three areas leaders can consider: creating transparent and explainable processes for generating AI-powered insights, establishing clear governance, and building trust within the workforce.”

In building an AI-augmented workforce and ensuring businesses can derive the greatest benefit from AI systems, one thing is clear: It is critical for organisations to focus on strategic change management to build AI trust within the workplace. To be effective, AI-driven decision intelligence must be underpinned by a strong foundation of data literacy, as well as proper training and upskilling.

Only through the combination of quality data, diverse human intelligence, and an accessible robust governance process will AI become the force behind automated business decision intelligence capable of driving the company forward.

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