The Competitive Advantage of AI Digital Transformation Initiatives

AIManager360 - Oscar Civantos and AIManager360 research team

When OpenAI launched ChatGPT in November 2022, it rapidly brought AI into mainstream consciousness, but the implementation of AI by businesses had been quietly underway for years. AI is now everywhere - it has reshaped how companies manage their customer service requests, hire new employees, process orders, and streamline their operations.

In this article, we’ll explore examples of how successful AI implementation has transformed organisations across various industries and business functions, and examine how AI Business Intelligence platforms can help businesses kickstart their AI strategy and make sure they don’t miss out on a critical competitive advantage.
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1. Generative AI in Retail

The retail industry has been one of the first to implement AI initiatives to deliver advanced personalisation to existing and potential customers. In fact, hyper personalisation has become so ubiquitous that now, according to a survey conducted by McKinsey, 76% of shoppers become frustrated when retailers offer them a generic shopping experience that doesn’t feel tailored to them.

Supply chain management, too, has been transformed thanks to AI becoming more accessible. From predicting demand to inform stock forecasting, to robotics entering warehouses, many retailers have completely revolutionised their business models to make the most of new technologies. 

^{AI and Personalised Shopping Experiences} 

We have all had the experience of thinking about buying something, only to see ads for that exact item appear shortly after, leading us to suspect phones to be “listening” to our conversations. In reality, these targeted ads are often a result of AI-driven algorithms that track browsing behaviour, search history, and online activity to predict user interests.

The ROI conversion statistics for hyper personalisation in ecommerce confirm that this strategy works: companies that are that thrive at personalisation earn 40% more money from these activities than the average competitor.

Giants like Amazon and Alibaba were among the first to introduce AI-driven suggestions to influence purchasing decisions, but more and more small and medium size retailers are following their lead and experimenting with AI across their online stores and advertising efforts.

Some have even created an entire business model around it: German-born Outfittery provides AI-powered styling advice based on customers’ profile._‍

^{Supply Chain Optimisation} 

The complex supply chains in retail involve numerous stakeholders and moving parts. With AI, retailers can optimise stock management with advanced forecasting, based on factors such as trends, local events, and even weather.

American supermarket giant Walmart, for example, leverages an AI-powered inventory management system that reallocates products according to demand forecasts.

If a certain product is being sold in high volume in a specific region, and staying on the shelves in another, the company can automatically organise the repositioning of inventory to the area with higher demand.
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2. Generative AI in Hiring and Human Resources

AI is having a profound impact on almost every industry, but is also being used transversally to increase the efficiency of single business functions. HR and recruitment is one such example, with many companies automating repetitive tasks and enhancing decision making with data-driven analysis.

^{AI-powered recruitment}

Enterprises are often recruiting at scale, which requires recruiters to sift through hundreds, sometimes thousands of CVs. AI can do this in minutes, significantly reducing the time recruiters need to spend on this time consuming task and freeing up their time to invest in subsequent stages of the recruitment process.

But it’s not just CV screening that can be automated - companies like Unilever use AI to screen the answers candidates give in short, asynchronous interviews, designed to assess certain specific skills and professional experience. This has resulted in a 75% reduction in the company’s time to hire, 50,000 hours, and over 1M saved, annually.

^{Reducing Bias} 

By virtue of being driven by data, AI also helps remove unconscious bias from the hiring process. Hilton Hotels, for example, partnered with a leading AI recruitment platform to develop custom assessments that evaluate candidates' cognitive abilities, personality traits, and job-specific skills.

The AI-powered assessments have enabled Hilton to identify top talent more accurately, leading to a 25% reduction in employee turnover and improved guest satisfaction scores.
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3. AI Business Intelligence Platforms

These examples from Retail and HR demonstrate how AI can drive significant transformations in various industries and business functions. It delivers time and cost savings, increased efficiency, and higher ROI, helping organisations get ahead of the competition.

However, making the wrong decision, such as choosing the wrong AI use case or implementing it poorly, can be extremely costly. A failed AI project can cost a company millions of dollars in lost investments, wasted resources, and missed opportunities for growth.

Gartner estimates that as many as 85% of AI projects fail to deliver on their promised value, underlining the risk for organisations to implement a hasty or ill-informed AI strategy.

Careful, data-driven planning, project prioritisation, cost and ROI analysis are essential for the success of AI automation initiatives. AI Business Intelligence (BI) platforms help organisations navigate the complex AI landscape by providing data-driven, unbiased insights to prioritise AI projects, monitor their success, and accelerate ROI.

They enable businesses to achieve competitive advantages in a fraction of the time and at a much lower cost than traditional consulting methods.

^{Prioritising High-Impact Projects} 

With the growing number of AI tools entering the market, selecting the right use cases can be challenging. AI BI platforms simplify this process by analysing a company’s data and business needs to identify the most promising AI projects.

For example, in retail, the platform might evaluate whether hyper personalisation or supply chain would yield the highest return, how much either project would cost, and how quickly it could be implemented. By using AI-driven insights, these platforms help businesses focus on the initiatives that will have the greatest results, avoiding costly trial-and-error approaches.

^{Monitoring and Accelerating ROI}

After initial implementation, continuously monitoring the results of AI initiatives is essential to ensure ROI. It is a common problem of AI SaaS tools: poor change management and low internal adoption lead companies to pay for a service they don’t fully leverage for years, wasting resources and gaining minimal benefits.

AI BI platforms provide real-time monitoring of AI projects performance, tracking KPIs specific to each organisation and forecasting future results. This allows for adjustments that ensure the success of AI initiatives and helps digital transformation leaders demonstrate the success of their projects.

^{Ensuring Compliance and Reducing Costs}

With legislation around AI in continuous evolution, AI implementation requires companies to abide by standards that often vary from country to country. This can pose a risk in the form of fines and reputational damage. AI BI platforms recommend tools that are compatible with the regulatory frameworks applicable to a specific industry and region.

For example, in a finance company adopting AI for fraud detection, the platform could automatically assess whether the AI complies with data privacy regulations. This significantly reduces the risk of incurring in penalties and the cost of expensive internal oversight.

^{Minimise Bias}

AI BI platforms analyse AI implementation initiatives suitable for a certain company based on such company’s data. This objective analysis reduces the risk of decisions being made based on intuition. This leads to evidence-based prioritisation, more accurate impact assessments, and faster implementations.
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AI Implementation, Done Right

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While the potential of AI is clear, achieving positive outcomes requires careful planning, prioritisation, and monitoring. AI BI platforms provide a solution by helping organisations identify the most impactful AI projects, track success in real-time, and ensure compliance, at a fraction of the cost and time of traditional consulting.

As new tools continue to enter the market, and as AI solutions become more sophisticated, these platforms will be increasingly better positioned to empower companies to make sense of this complex landscape and continue to stay ahead of the competition in a rapidly changing market.