AI Adds Efficiency: Overcoming Challenges With Silos

AI Adds Efficiency And Your Silos Ruin It

by George Humphrey — 3 months ago in Artificial Intelligence 3 min. read

Artificial intelligence (AI) is one of the most disruptive technology developments since the advent of the internet. However, the adoption and implementation of AI adds efficiency is moving significantly faster than the internet ever did. This technological advance is adding efficiencies to many aspects of business, and benefits are already emerging. For businesses to successfully navigate this evolution, they need to quickly adapt and implement new business models and strategies. Sadly, most are struggling.

For example, a technology company invests in a generative AI solution for creating content for its education services team. That team sees a 30% increase in efficiency, making resources available for other priorities. But the company doesn’t know how to use these newly available resources. And the successful learnings from this project have not been shared in their other AI initiatives, which are lagging behind. In turn, the business is not seeing a boost to their bottom line.

The reality is that the world has been caught flat-footed in implementing AI technology. Whether due to world economics, poor business strategy, or a variety of other factors, businesses around the globe need to refocus to implement this new technology.

TSIA’s research shows that more than three-quarters of technology companies are in the process of investing in AI, but more than 70 percent do not have an executive leading this work. While many companies have a substantial amount of pilot AI projects underway, over 80 percent have not created a system for sharing learnings and best practices between programs. Worse, less than 30 percent are seeing fiscal benefits.

This is indicative of businesses that are scrambling to embrace the new technology but are doing so without an organized and strategic approach that will result in improved business operations, reduced costs, and improved customer experiences.

First, business leaders need to understand that there are three core dimensions of AI to improve business operations. All of them show clear opportunities to add efficiencies. They are:

● Data-Driven Decision Making

● Efficiency and Cost Reduction

● Enhanced Customer Experience

Data-Driven Decision-Making

AI can drive informed, data-driven decision-making across all aspects of a business. A stable, company-wide data science and analytics function is necessary for any artificial intelligence capability. AI can analyze vast amounts of data quickly and accurately, providing valuable insights for decision-making. Data-driven decisions should lead to better outcomes, improved competitiveness, and increased profitability.

For this dimension of AI to be applied requires specialized data science and data analytics functions. Simply put, data science helps an organization understand where data-driven decision-making could be applied. Then, data analytics helps organizations understand where data-driven decision-making should be applied.

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Efficiency and Cost Reduction

AI can automate some tasks, streamline operations, and optimize resource allocation, which are tasks that previously were only effectively performed by human beings. These abilities are primarily successful through machine learning (ML) and robotic process automation (RPA).

Through ML, enormous volumes of data are used to train algorithms through a wide range of approaches to identify patterns where the process becomes known and the outcomes become expected. Then RPA applies the ML data to automate tasks, with improved efficiency and fewer errors.

Enhanced Customer Experience

Finally, AI has the ability to effectively engage customers and deliver high levels of customer satisfaction. Natural language processing (NLP) and Generative AI are quickly becoming effective tools to enhance customer satisfaction.

NLP solutions focus on the interaction between computers and humans, or human language. By treating this information as data, a digital system is able to understand, interpret, or act on spoken or written information.

Generative AI is an emerging body of artificial intelligence that leverages the previously mentioned aspects of the technology. By leveraging data science and machine learning, AI can be used to create content that is often indistinguishable from human-generated content.

The business potential for these tools is increasingly apparent, and every day we see increased investments in this technology. A best practice is to implement a centralized team that owns the strategy and technical execution plan for AI. The role of this team is to understand the three dimensions of AI that we’ve previously discussed. This team will be responsible for directing the AI strategy across the enterprise, identifying emerging AI opportunities, managing implementation progress, and achieving positive, measurable results.

AI has the potential to accelerate data-driven decision-making, improve operational efficiency, reduce the cost of operations, and accelerate the improvement and advancement of compelling customer experiences. Unfortunately, most companies are trying to tackle this with a fractured approach to implementation.

Make no mistake, all business model transformations have a well-earned reputation for not meeting their goals and objectives, over-running costs, and frustrating customers and employees when using a fractured approach. AI has the potential to be one of the greatest technological evolutions in history, and it is imperative that businesses take a smart, holistic approach to navigating this evolution if they hope to come out on top in the coming years.

George Humphrey

George Humphrey serves as a distinguished vice president and managing director of research and advisory for TSIA. Touting more than three decades of technology business knowledge, Humphrey is a valued resource and advisor to many of the world’s most successful technology business ventures. As a research leader at TSIA, Humphrey’s insights are regularly leveraged by Fortune 500 companies through his advisory work, public speaking engagements, research reports, and publicly shared content on a variety of evolving business topics.

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