As we enter 2025, we can clearly see AI has made significant, and even transformative, inroads into every sector. Among enterprises, merely the adoption of AI is no longer considered a major digital transformation achievement. Instead, enterprises know that they need to focus on scaling their AI initiatives to drive foundational change across their business landscape. Clearly, having an AI chatbot integrated into all customer channels to handle queries isn’t enough anymore.
Companies today are looking for ways to integrate capabilities like generative AI into deeper elements of their core business operations to not just improve productivity but to dramatically change how they operate. And it’s working! For instance, studies show that companies adopting GenAI have witnessed nearly 42% improvement in outcomes related to their customer experience.
AI isn’t a trend – it’s now a business imperative!
Today AI-powered systems can handle a wide range of creative, intelligent, and innovative tasks. These range from content creation in multiple formats to even coding and powering robotic movements in automated factories and warehouses. The adoption of AI capabilities is helping businesses of all sizes achieve real value across several crucial areas. These span improved customer experience, greater operational efficiency, better-informed decision-making, and even the creation of new business models.
However, is the hype overtaking the reality?
It is extremely important for business leaders to understand what AI-enabled transformation can bring to their operations and, more importantly, how to mitigate pitfalls in the journey.
The potential opportunities for AI-enabled business transformation
Better decision systems
The ability of AI to crunch structured as well as unstructured data at unprecedented volume to extract insights hidden deep within is the secret to unlocking more informed decision-making. This provides businesses with better insights, driving their ability to take more appropriate actions faster. In today’s competitive business landscape, speed and accuracy of decision-making can often be the defining competitive edge needed to dominate markets.
Build new revenue streams
AI systems can be leveraged to create and deliver services autonomously thereby adding a new chapter in the value chain of businesses. For instance, a retailer can add a new digital personalized sales channel completely powered by AI. Designed as a conversational bot, it can interact with potential customers via social media or instant messaging and execute the full sales cycle from gathering preferences to delivering suggestions for best-fit products, extending to customizing offers and allowing users to complete the purchase cycle. Then AI could power the systems tasked with executing delivery fulfillment workflows automatically. None of these stages would depend on human intervention. Today, AI can open whole new revenue streams and business models for retailers.
Eliminate risks
The high level of intelligent analytical processing capabilities of AI systems will help enterprises understand and mitigate risks in the business faster and more effectively. Continuous monitoring for cyber threats, anomaly detection in data behavior, predicting the impact of changes, etc. will help organizations sight and fight threats. This will help them avoid disruption and eliminate risks proactively.
Bring cost efficiency
Businesses that depend on large transactional systems often find it hard to control their resource span to manage the scale of operations involved within their digital landscape. With AI capabilities, however, it is possible to optimize resource allocation intelligently. At the same time, AI can parallelly handle large volumes of transactional processing with contextual and factual interpretation. This eliminates the need for manual processing of insights. These AI-driven systems can directly power decisions and hence reduce the cost involved in the process. Automation by AI also allows businesses to free up their key people to handle more important activities, without having to focus on mundane repetitive actions.
Avoiding the pitfalls
Even though AI brings so many opportunities for businesses to leverage, the journey isn’t always a successful one for everyone. Many companies are not prepared to handle the organization-wide changes and operational complexities that come with the growth of strategic AI penetration in their key business decision frameworks. Studies by BCG show that nearly 74% of companies that adopt AI initiatives cannot derive tangible value or scale from their investments.
The root cause of AI pitfalls – lack of a strong data foundation
One of the major reasons for low success rates in AI adoption is enterprises’ inability to set up a solid data foundation to support and grow AI. Data is the necessary fuel for any AI system. The accuracy, efficiency, and effectiveness of AI capabilities, be it predictive analytics or generative AI, etc., depend heavily on how algorithms can train AI models with the most relevant data.
Building a resilient and reliable data foundation requires a tremendous amount of effort in adopting the right data management strategy, fine-tuning the most accurate and personalized data models, setting up data acquisition, transit, and storage networks and infrastructure, and adding the right intelligence to extract accurate insights and much more. Additionally, enterprises’ use of multi-cloud environments adds another layer of complexity to the data availability and governance mix. Taking the right direction of building a data strategy aligned with the growth objectives of AI-enabled transformation is critical for enterprises to succeed in the AI race. Partnering with a specialist solution provider like Trinus can be the first step for enterprises looking to build a data-driven business that can readily embrace AI and other emerging innovations at scale. Get in touch with us to know more.