AI’s Disruptive Potential in Business

In the ever-evolving landscape of business, artificial intelligence (AI) stands as a revolutionary vanguard, transforming mere possibilities into tangible solutions. The seismic shifts catalyzed by AI within organizations transcend the traditional boundaries established by data analytics and operational research, yielding significant results.

Think of the evolution of data and analytics in business as a journey. First, we had statistics, which gave us basic tools like dashboards and ways to test ideas through carefully designed experiments. Then came operations research, helping businesses plan better by figuring out how to allocate resources and maximize profits. More recently, machine learning, a branch of artificial intelligence, has taken us a step further by making smarter predictions—like which products customers might want to buy next or how risky a financial decision might be.

And now, we’re seeing the rise of generative AI, which can create things like text, images, and sound based on the data it’s given. These latest advancements—machine learning and generative AI—are opening up exciting new ways for organizations to improve their performance. 

These advancements are not incremental; they are disruptive, in part because they allow innovations to be introduced in a manner that breaks the normal, linear, incremental approach to improving process. As we unpack the transformative power of AI, we spotlight three pivotal strategies it is used to supercharge organizational capabilities.

In the past, companies took their time to move from paper to digital, often through big projects aimed at transforming how they did business. Once they had their data in digital form, they would then use various tools and models to make sense of it and plan their strategies. These two steps—going digital and planning strategically—were often seen as separate tasks.

But times have changed. AI has become the bridge that connects these two steps. Imagine having a super-smart assistant that not only keeps track of all your data but also instantly tells you what it means and how you can use it to make better decisions. That’s what AI does. It takes all that digital data and turns it into insights you can use right away, making the whole process much more efficient. In enabling this to happen, the data not only supports the strategic decision making, it becomes part of the strategy itself.

So, what we’re seeing now is a blending of the old steps into an integrated process. With AI, the line between collecting data and using it to plan your next move has become almost invisible. This means businesses can make smarter, faster decisions, all thanks to the power of AI.

• Skill-based HR strategies — AI is enabling organizations to redefine employees’ jobs from fixed sets of tasks to flexible application of skills which are matched with different needs in the organization on an ongoing basis. Identifying the skills employees have, the skills that projects or roles require, and matching them accordingly make jobs more fulfilling through introducing choice and variety and provide incentives for employees to learn new skills to access different opportunities. It also makes the use of human resources much more efficient, as the usual combination decoupling the sets of tasks often imperfectly combined into fixed roles enables an organization to use more of an employee’s capacity and skills. This is only possible because of the ability of AI-driven capabilities to capture and facilitate the dynamic matching necessary between employees’ abilities and capacity and the organization’s needs.
• Supply Chain Optimization — Companies like Walmart and Procter & Gamble use AI to analyze real-time data from multiple sources, including weather patterns, historical buying trends, and warehouse stock levels. This allows them to predict demand more accurately and plan their supply chain strategy accordingly. The result is reduced costs and increased efficiency.
• Human Resources Planning — AI can analyze employee performance metrics, market salary rates, and even employee satisfaction surveys to help HR departments make data-driven decisions. For example, IBM’s Watson can predict when employees are planning to leave, allowing companies to take preemptive action to retain talent, thereby informing long-term HR strategy.
• Market Expansion Strategy — Companies like Netflix use AI to analyze customer behavior, preferences, and even cultural trends in different regions. This data informs their market expansion strategies, helping them decide not just where to launch, but what kind of localized content to offer.
• Competitive Analysis — AI tools can scrape vast amounts of data from competitors’ public records, social media, and customer reviews. This data can be analyzed to identify market gaps, potential areas for differentiation, and emerging consumer needs, thereby informing a company’s competitive strategy.
  
• Sustainability Planning — Companies like Unilever are using AI to analyze environmental data and consumer sentiment around sustainability. This informs their long-term strategy, helping them plan new, eco-friendly product lines and sustainability initiatives that resonate with their customer base.
• Financial Risk Assessment — Financial institutions use AI to analyze market trends, geopolitical events, and even social media sentiment to assess the risk levels associated with different kinds of investments. This informs not just individual investment decisions but also the broader investment strategy.

Just as the onset of mobile phones allowed countries with low landline telephone connectivity to bypass land connections altogether, AI allows companies that are only starting on the data journey to bypass several intermediate layers of analytics products. Instead of a linear progression through a slew of models, AI enables businesses to skip several developmental steps and arrive at final solutions faster.

AI’s ability to leap-frog traditional developmental stages is akin to a disruptive innovation. Businesses, especially startups and SMEs, can now bypass expensive and time-consuming phases of data analytics and go straight to implementing sophisticated solutions.

• Consider the traditional customer service model which primarily focuses on training customer service agents in large call centers to handle queries quickly. Now, thanks to large language models (LLMs), organizations can restructure this model. They can manage multiple interactions simultaneously, making the customer service experience more efficient and agile.
• In healthcare, AI-powered diagnostic tools are enabling clinics in remote areas to provide advanced medical care without the need for extensive medical infrastructure. These tools can diagnose conditions like diabetic retinopathy and skin cancer with high accuracy, bypassing the need for specialized medical equipment.

AI serves as a catalyst for innovative problem-solving. It not only automates tasks but also identifies gaps in existing processes, offering solutions that can revolutionize entire industries.

• Online Retail — Fashion brands are integrating AI tools that use photos to determine the right size for online shoppers, drastically reducing returns due to size discrepancies.
• Manufacturing — The conventional approach to equipment maintenance involves using regular schedules to prevent malfunctions, which can sometimes lead to premature replacements. AI offers predictive maintenance, analyzing diverse inputs to determine the optimal maintenance time. This approach not only pre-empts potential malfunctions but also reduces unnecessary costs.
• In the field of Human Resources, AI-powered tools are being used for talent acquisition and management. These tools can analyze thousands of resumes in seconds and predict candidate success, thereby reducing the time and cost of hiring.

As AI continues to permeate various sectors, its impact extends beyond mere automation or data analytics. It is redefining the operational and strategic paradigms of organizations, offering unprecedented advantages in efficiency, innovation, and problem-solving. The disruptive potential of AI is not just an incremental improvement but a revolutionary change that benefits both businesses and consumers alike.

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