The High-Rise of AI Transformation: Synergizing Both Infrastructure & People for Greater AI Maturity - Aberdeen Strategy & Research (original) (raw)
The High-Rise of AI Transformation: Synergizing Both Infrastructure & People for Greater AI Maturity
Leveraging AI in business is like erecting a skyscraper, stretching to new heights, and pushing the limits of what’s possible. Its glittering upper floors filled with automation, insights, and data-driven decisions draw the eyes of everyone passing by, but it takes a lot of hard work and planning to create and upkeep something so miraculous.
Skyscrapers today are built with high-strength concrete cores and specifically designed reinforcing bars, and these infrastructure features allow for the external walls to be thinner to reduce costs while improving safety and stability. Similarly, AI can fail if engineers don’t build a reinforced technology backbone, complete with high-quality data management, cybersecurity, and other critical IT capabilities.
Aberdeen Strategy and Research conducted a survey with 341 business professionals involved in AI strategies at their organizations to learn how they are approaching AI and what their technology backbones look like. When asked to rate their maturity in key data management and IT capabilities on a 1–5 scale of Basic to Optimized, roughly 60% rated themselves as Advanced or Intermediate across each area, with about 20%–30% still only rating their infrastructure as Basic or Functional.
Self-Reported Technology Infrastructure Maturity
The entire data lifecycle from data capture through cleansing, prep, integration, and governance is critical for AI success. If AI algorithms are attempting to process poorly organized or inaccurate data, they will identify false patterns, come to the wrong conclusions, and supply decision-makers with recommendations that may not be best for the company. Storage / backup / disaster recovery capabilities are helpful for AI algorithms to continue running when data is lost, and comprehensive app development capabilities ensure AI can be easily leveraged within existing applications. Lastly, risk management, privacy, and compliance measures are important to ensure your algorithms are resistant to cyber threats.
In addition to technology, Aberdeen’s research also investigates the human side of AI. Respondents were asked about the availability of certain resources or deployment of certain strategies to increase AI awareness and knowledge within their organizations.
Current Usage of AI Workforce Capabilities
Businesses need to prepare their workforces to handle data for AI processing, develop and update AI algorithms, and make decisions based on results from AI. Based on the percent of business leaders rating the top two skills that will be most critical for working with AI, it will be crucial to build up analytical judgment (37%), flexibility (30%), and collaboration (26%) among employees. Currently, only 31%-38% of companies currently have programs for awareness training, commitment from leadership, hiring plans, and line-of-business training to engage their workforce around AI. As AI becomes more prevalent in day-to-day business, it’s likely that we’ll see these workforce capabilities improve alongside technology.
By segmenting respondents by their infrastructure maturity and their workforce maturity, Aberdeen identified 3 main approaches to optimize AI usage: technology-first, people-first, and balanced. Using the skyscraper comparison, there are three ways to build something as grand and impressive as an optimal AI strategy.
To Optimize AI Usage, Build Both a Technology Backbone and a Workforce Strategy
- About 1 in 3 companies take a technology-first approach and allow their employees to adapt as they build out AI capabilities (see the blue line in the figure below). They may have low or average maturity in people-related capabilities, but they are making progress on their technology infrastructure. This is a good approach if you trust your workforce to keep up with the speed of innovation and learn quickly. These organizations focus on building the foundation and frame of their skyscraper before talking to future residents and staff about what they need.
- In contrast, 15% take a people-first approach by preparing their workforce ahead of investments in solutions (yellow line). These organizations are higher on the workforce maturity scale, but they have yet to adopt critical technology enablers that will allow them to become AI powerhouses. This is a good approach for those who don’t yet have the budget to dedicate to AI and who want to be more conscious about giving their workforce what they need to be successful. These organizations take more time during the construction process to ensure they work with future residents and staff to include features they care about and properly prepare them for move-in.
- However, more than 50% of respondents aim to achieve their AI goals by taking a balanced approach to their investments in infrastructure and people (green line). This means that they develop their technology and workforce at relatively even paces, allowing them to adjust as they build. They want to push progress forward on their skyscraper while still checking in with future residents and staff to learn about their ideas and needs.
Whatever approach your business decides to take, it’s clear that both technology and people are an important part of a successful AI strategy, maybe even more important than they are for constructing a skyscraper. High-rise buildings teach us a lot about all the moving parts required to create something incredible while still keeping structure and flexibility in mind.
Skyscrapers, once built, need staff to attend to them and residents to benefit from them. Leaders should constantly be checking in with their workforce to ensure their AI-enabled applications are easy to manage and provide the most value. Skyscrapers also need to be updated to keep up with technological advances for features like high-tech keypads, security, heating and cooling, and others. AI algorithms similarly need to keep up with the pace of innovation, albeit on a daily basis rather than a yearly one. Approaching AI strategies with the same careful thought and grand plans as a skyscraper can lead businesses to achieve great things!
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(INFOGRAPHIC) Unlocking AI Transformation: Synergizing Both Infrastructure and People for Greater AI Maturity
This infographic (along with Sarah's video) sheds more light on the article. View this infographic to explore AI infrastructure and workforce maturity and discover the strategic paths to unlock AI excellence.
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Sarah is the Manager of Aberdeen’s Research and Data Operations team. In addition to overseeing Aberdeen’s survey and content creation processes, she conducts research focused on the intersection of manufacturing and emerging technologies as well as the data systems companies have in place to streamline operations and make informed decisions. Sarah holds a bachelor’s degree in Mathematics with a concentration in Statistics from Colby College.