Are we in the midst of an AI-led revolution? With how things have transpired over the last few years and especially since the leap to prominence of large language models (LLMs), it's hard to think otherwise. 

McKinsey stresses that there are "plenty of opportunities for growth as organizations increase their adoption of AI and their spending on the technology." In fact, the consulting giant outlines that despite the increased investment, there are several avenues where market penetration is low or the impact only nascent. For instance, 50-60% of companies have deployed AI but are struggling to scale it.

In line with that, McKinsey has included Applied AI as among the top 15 technology trends for 2023. Using Applied AI, a good portion of digital service touchpoints (including voice assistants) can improve usability, personalization, and customer conversion to deliver real business impact.

As the next-level AI technology, Applied AI can influence many industries, especially the following:

• Pharmaceuticals

• Healthcare

• Transportation & logistics

• Automotive

The question is — are we ready to make the leap from AI to Applied AI? What does that entail? What are the benefits? Let's discuss.

What Is Applied AI and How Does It Improve Traditional AI?

Applied AI is the application of AI technology in the real world. For instance, when applied to cloud-powered data analytics, Applied AI can deliver valuable business insights and outcomes.

Despite their immense potential, only 12% of "traditional" AI projects make it into the production phase. Most AI projects fail due to a lack of reproducibility, scalability, and leveragability. Applied AI encompasses all tools needed to operationalize AI from the experimental stage to the production stage. In addition to developing and deploying AI models, Applied AI operates on data and delivers business results.

How does it improve "traditional" AI technology? We all know that AI and ML make machines more "smart." However, this is more of a concept. In reality, it is Applied AI that powers the real-life capabilities of AI and ML. For instance, when working with data analytics, Applied AI enables faster data processing and deploys "intelligent" algorithms for analytics tools to detect accurate data patterns and insights.

Here are some of the ways in which Applied AI technology can transform data analytics:

• Use machine learning algorithms to predict business outcomes and market trends.

• Eliminate manual errors and offer more accuracy in business intelligence (BI) initiatives.

• Automate report generation, thus making data easy to comprehend for business users.

Business Benefits of Applied AI

Applied AI delivers a range of business benefits for enterprises across industry segments. 

1. Improves Business Decisions

Forbes has previously reported that 95% of enterprises need to process unstructured data across operations. In the age of data-driven decision-making, Applied AI enables machines to arrive at "human-like" decisions by reducing errors and accurately predicting outcomes. 

For instance, Applied AI algorithms can drive decisions in data-sensitive business areas such as analyzing employee productivity, generating financial reports, and predicting customer churn rates.

2. Improves Efficiency and Productivity

According to Gartner, 85% of AI projects deliver erroneous results due to data bias, incorrect algorithms, or human errors. High-quality data is necessary to deploy any AI model successfully across any use case.

Applied AI effectively maintains consistent data quality from the training to the production stage. Through proper verification and cleaning, high-quality data is made available when deploying the AI model in the production environment. This directly translates into improved business efficiency and productivity, reducing manual errors and human bias. 

3. Augments Human Efforts

Applied AI technology can augment human intelligence instead of replacing it. For instance, through data analysis, it can improve human decision-making skills. Human resources can also leverage Applied AI to improve their capabilities, especially in the fields of data science and analytics.

For example, using consumer data in the retail sector, Applied AI tools can help optimize retail store layouts and product placements. Similarly, healthcare providers can receive personalized recommendations based on the patient's medical history. Besides, AI-led automation can free up the human workforce from tedious manual tasks and help them devote more time to higher cognitive work.

4. Increases Business Revenue

According to McKinsey, Applied AI technology is positively impacting the company's bottom line. In their 2021 report, 27% of respondents reported AI as the reason behind 5% of their EBIT. 67% reported an increase in revenues after AI adoption, while 79% reported a drop in business costs.

Effectively, Applied AI is increasing profitability and reducing costs by addressing complex business problems with its machine learning capabilities. This includes business problems across functions, including:

• Customer support

• Demand forecasting

• Financial fraud

• Customer behavior prediction

5. Bridges the Gap Between the Physical and Digital Worlds

Traditional AI systems have worked optimally in the digital sphere. However, they have had limited benefits in the physical world. Applied AI has successfully bridged this gap.

Among the key applications, Applied AI is used to analyze transport-related data from connected sensors and cameras. AI algorithms can easily optimize real-world traffic flow, reduce traffic congestion, and enhance road safety. Similarly, Applied AI is being used to improve the environment by optimizing energy consumption and reducing waste.

Make the Leap from AI to Applied AI with Recode

Going back to the aforementioned trends outlook by McKinsey, the consulting firm stresses how AI continues to push towards new frontiers of innovation. According to this report, the potential economic value of Applied AI ranges between a whopping $17 trillion and $26 trillion.

At Recode Solutions, we are driving innovation through our AI-led automation services. Besides, as AI advances to make enterprises smarter, it is also contributing to the generation of massive volumes of data. This is where our cloud-powered data analytics services work for unlocking value from structured and unstructured data assets. 

Here are some ways our data services can help in:

• Identifying business opportunities and use cases

• Democratizing data for widespread usage

• Using advanced visualization and predictive analytics

We can help you make the leap from AI to Applied AI. Contact us today to learn more.