While the impact of Artificial Intelligence (AI) on businesses is undeniable, the roadmap to harnessing its power is intricate – requiring a blend of strategic insights, collaboration and ethical considerations.

A new study by WNS Triange and Corinium Intelligence, The Future of Enterprise Data & AI, dissects the essential factors enterprises must consider to ride the AI wave with clarity and conviction. This study captures insights from 100 global C-suite leaders and decision-makers across AI, analytics and data, representing a broad spectrum of industries.

Let’s dive into some of the key strategies businesses should consider:

  1. Identify the Friction Points: To genuinely benefit from AI, businesses must prioritize value creation. It’s crucial to identify and address friction points within processes using AI. The strategy? Focus on specific problems where AI can genuinely add value rather than adopting AI for AI’s sake.

    It is essential to understand when and how to apply AI for maximum ROI. With business landscapes evolving, technology isn't just a tool but a strategic partner, and the equation of feasibility with value becomes paramount.

  2. Collaborate to Innovate: Organizations must recognize that while the allure of creating in-house solutions is strong, external expertise might be the key to unlocking rapid and cost-efficient value. Such external partnerships can often lead to quicker, more cost-effective solutions. With 65 percent of organizations prioritizing such partnerships for AI investments, it’s clear that collaboration will be central to AI's future.

  3. Leverage Quality Data as the Foundation: Vivek Soneja, Corporate Vice President – AI, Analytics, Data and Research at WNS Triange, rings the alarm on the quality of data. He articulates, “Feeding poor data into an AI system results in equally poor output. Enterprises need advanced data engineering and governance to maintain clean data, especially if AI will increasingly complement human decision-making in future.” The emphasis on maintaining data integrity, categorizing data for easier analysis and cleaning data to remove noise is more critical now than ever. 60 percent of the respondents say that ensuring integrity and quality is essential when preparing data for use in AI / Machine Learning (ML) and analytics.

  4. Adopt a Nuanced Approach to Scale AI: Scaling AI isn’t just about expanding its use but ensuring its consistent effectiveness across a growing expanse. Our research outlines challenges like building trust in AI systems, ensuring quality data for AI training and managing costs.

    Ravindra Salavi, Senior Vice President – AI, Analytics Data and Research at WNS Triange, ties these challenges back to the foundation of AI initiatives, suggesting a holistic involvement from various stakeholders, not just the tech teams.

  5. Navigate the AI Accountability Maze: Data security and privacy concerns are scaling as quickly as AI adoption, especially in sectors where compliance and regulation are stringent. With challenges like model poisoning, data privacy during processing and regulatory compliance, businesses must tread cautiously. A staggering 72 percent of leaders express deep concern about AI decision-making accountability.

    “We need clear strategies and policies to ensure we’re not infringing on privacy or ethics. With the vast amount of data available, it’s possible to know intricate details about a person’s life. Organizations must establish boundaries,” says Soneja. As AI becomes more intertwined with our lives, ensuring its responsible use is not just a business imperative but a societal one.

The AI-powered future is real. However, it’s up to today's enterprises to navigate it with foresight and responsibility. By focusing on real-world problems, collaborating wisely, prioritizing data quality and addressing ethical concerns head-on, businesses can unlock AI's true potential.

WNS Triange’s extensive research report, The Future of Enterprise Data & AI, delves deeper into the intricacies of AI in the modern enterprise, offering actionable insights and expert perspectives. Access the full report now.

About WNS Triange:

WNS Triange powers business growth and innovation for 200+ global companies with Artificial Intelligence (AI), Analytics, Data and Research. Driven by a specialized team of over 6000 analysts, data scientists and domain experts, WNS Triange helps translate data into actionable insights for impactful decision-making. Built on the pillars of consulting (Triange Consult), future-ready platforms (Triange Nxt), and domain and technology (Triange CoE), WNS Triange seamlessly blends strategy, industry-specific nuances, AI and Machine Learning (ML) operations, and intelligent cloud platforms.

Driving a futuristic edge are WNS Triange’s modular cloud-based platforms and solutions leveraging advanced AI and ML to provide end-to-end integration and processing of data to actionable insights. WNS Triange leverages the combined strength of WNS’ domain expertise, co-creation labs, strategic partnerships and outcome-based engagement models.

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