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AI and the Future of Business: Overcoming Obstacles to Unlock a Trillion-Dollar Revolution

The impact of AI is unmistakable in every swipe on our smartphones and every click on our laptops, subtly shaping our digital interactions. It recommends articles, directs investments and refines our travel routes. This extends beyond mere personal benefits — AI is poised to significantly drive the global economy forward, with GenAI potentially boosting it by an impressive $13 trillion. This compelling economic benefit is a clear call to businesses: evolve with AI or risk falling behind.

Already, more than half of global companies are heeding this call, ready to amplify their investments to harness AI’s full economic potential.

Obstacles Mark the Path to AI-First Status

However, being an AI-first company takes a lot more than just updating software or getting the latest solutions; it takes a complete transformation of how businesses function, where we put the right focus, how we use technology, and the scale at which we innovate and operate.

Enterprises eager to integrate AI into their operations might first meet several critical speed bumps.

Endless Disruption:

AI is constantly evolving, accelerating transformations across sectors. Take banking, for instance. Its future is veering towards being a deeply personalized, intelligent, and omnichannel experience.

Imagine this: Sam, a working professional, seeks health insurance through her bank. Instead of the usual rate assessment, she receives a 2% discount on her premium, a perk dynamically calculated from her gym attendance and sleep quality. All this is streamlined by GenAI, slashing operational costs while delivering a hyper-personalized omnichannel experience.

Banks that harness AI and rapidly constantly evolve with it will be on track for exceptional growth.

On the other hand, those unable to keep pace stand to lose out significantly. The message is clear: AI is consistently transforming industries. Matching AI’s pace ensures robust growth and augmented shareholder value. Failing to do so, however, risks stagnation. The performance gap AI widens is undeniable.

SuboptimalTech Investments: 

When it comes to tech investments, it’s easy to get caught up in the latest and supposedly greatest, but that’s leading many companies down a costly path. Take this bank in North America as an example: they built a web of over 1,000 systems that are costing them $2 billion in ‘technical debt’ – the price we pay later for quick fixes made in a rush. This technical debt represents not just a financial strain but a significant obstacle to achieving a complete digital transformation.

A study indicates HR professionals navigate between three to six applications to complete a single task, a clear symptom of tool redundancy. Not only is the quantity of tools overwhelming, but the quality also leaves much to be desired, with reports of user-unfriendly interfaces and inconsistent performance.

The underlying issue is a misalignment of technology and business strategies. When we rush into new tech investments without a game plan that’s aligned with our larger business goals, we end up with a mishmash of old and new systems. It’s like trying to fit pieces from different puzzles together—impossible and expensive.

To avoid this, we need to think of digital transformation not as buying the latest tech but as a strategic rethinking that involves the whole company. It’s about choosing tools that integrate smoothly, keep our data in one piece, and make sure we are agile and can adapt as needed. That’s the kind of strategic thinking that will put us ahead and keep us there.

Pilots that don’t scale:

Pilot projects are popping up in boardrooms, each promising to be the next big thing in business transformation. But numbers show that despite the initial enthusiasm, a significant 70% fail to scale across the enterprise. Financial restrictions, operational complexities, and resistance to change clip the wings of widespread digital adoption.

These challenges mean that while certain areas of a business might enjoy the benefits of digital innovation, the impact doesn’t extend across the entire operation to user experiences.

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This isn’t just about missing out on a few opportunities for improvement. It’s about the bigger picture: staying competitive. As digital initiatives fail in scaling up, businesses leave gaps for more tech-savvy disruptors to leap ahead. In short, we’re witnessing the paradox of progress: abundant technological advancements, yet a struggle to harness them for transformative change.

The great wall of Silos:

Take Sam’s case, where her dedication to fitness nets her a customized discount on health insurance, showcasing the power of AI to forge partnerships across banking, insurance, and health tech. This is the benchmark for an AI-first company: hyper-personalization at its finest.

However, what’s striking is that while this kind of inter-industry connectedness is the goal, many companies are struggling to achieve this seamless integration within their own walls. Silos are stifling the flow of information between people, processes, data, and tech, costing up to 30% of potential revenues and hindering the kind of integration essential for AI to thrive.

If Sam’s health data doesn’t speak to her financial profile, the opportunity for customized service vanishes. In this disconnect, the aspiration to be AI-first becomes unattainable. Breaking down these silos is an operational adjustment and a strategic imperative to unlock AI’s transformative promise.

These obstacles teach us an important lesson. Companies must ensure that their technology investments are not just new but right — right for their people, processes, and long-term strategic vision. Only then can they unlock the full potential of digital transformation and avoid the pitfalls that have ensnared many in a costly cycle of technical debt, unscalable pilots, and an overall disconnect in the enterprise.

Breaking Ground for a Customer-Focused, Automated, Data-Driven Future

Imagine a business landscape that not only adapts to market fluctuations but also forecasts them with pinpoint accuracy. This is the hallmark of AI-first enterprises.

Consider a leading supply chain organization that seamlessly predicts disruptions, adjusts its routes, and changes its course in real-time with the help of connected data systems, analytics, and AI.

How is this foresight achieved?

Their strategy is anchored in a customer-first or business-first philosophy. For them, transformation transcends digital—it’s about refining the entire user journey, enhancing it with technology, not being led by it. They place a premium on creating value through ecosystem partnerships and prioritizing human connections, tapping into contextual intelligence to guide their transformation efforts.

These organizations are steering towards a “hands off the wheel” future, where human ingenuity is the architect and sophisticated systems are the operatives.

Rather than focusing on cost reduction alone, they harness technology to amplify human capabilities. They aim for a high level of straight-through processing across essential customer journeys and business processes. By taking this approach, they don’t merely retrofit new technology into old systems. They design their processes with digital DNA from the outset.

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This strategic overhaul extends across all business divisions. In our supply chain scenario, it’s the convergence of logistics, inventory management, and customer service into a unified digital framework. Every department enriches the AI system, making decision-making processes not just quicker but also more intelligent and crafting a customer experience that is proactively engaging.

Does this mean an overhaul at the expense of existing investments?

Not at all. These businesses adopt a measured approach to reshaping their operating model. They strategically scale AI throughout their organization, taking a platform approach that connects all business operations, making digital engagement intrinsic to their identity.

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