Many companies get instinctively grouped as either technological leaders or traditional non-tech companies. This rash judgment often misses the evolution that many companies are going through to transform their business and industry through modern technological capabilities. People often assume that only the biggest tech companies such as Facebook, Google or Instagram are using advanced technologies like artificial intelligence (AI) and machine learning (ML) to drive their business. Since AI and ML have become easier to consume as cloud based services, we are seeing many organizations once thought to be non-traditional technology firms, begin to adopt these advanced technologies as well.
As organizations look to transform and stay competitive in increasingly digital markets, technologies like AI and ML are enabling employees to be more effective, make better decisions measured through data and respond more quickly to changing market conditions. This rapid response to changing markets is the largest driver for the use of AI. Employees no longer need to spot trends and react, but rather let the tools and algorithms respond as users’ needs change. AI and ML enable leaders in these non-traditional digital organizations to let their staff focus on the most powerful work activities where human input is required, and let the more trivial and less meaningful work fall to automation.
Four industries that we see rapidly changing due to AI include automotive, real estate, legal services, and education. Each industry is defined by traditional models that are reliant on growing numbers of employees to support growing customer bases. Each is also supported by a large number of lower-salaried staff to support the repetitive work of consolidating information and data for higher-up managers. These industries all share the same demand for higher quality data to accelerate projects throughout the organization.
Real Estate – The real estate market has always been driven by personal relationships that advance the immediate access to information for agents that are typically the most successful. Natural language processing and image recognition are being more widely adopted to facilitate the automatic analysis of closing documents and site images in order to expose inconsistencies. This rapid analysis of information enables brokers to quickly spot risks in deals they are negotiating and ensure their clients have access to the most accurate information when making decisions.
Education – The education space has historically been defined as students, arriving at a central location and taking set courses on established schedules. This model has worked but fails to include portions of the population who are non-traditional learners or have schedules that do not work with a traditional classroom environment. AI and ML are developing self-assessments which can create education plans specific to individuals’ needs.
Legal Services – Law firms have historically been built on a few partners, supported by a scalable team of paralegals, who focus on research, organization, and analysis of large amounts of data. AI brings the ability to automate these tasks for new lawsuits, as well as significantly cut down the time necessary to analyze large amounts of information at the beginning of the discovery process.
Automotive – The automotive industry is going through a major transition as it continues to deploy new technology to make driving more enjoyable, safer and efficient. Tesla currently has 1.3 billion miles of data related to automated driving.4 This gives them an advantage as they continue to improve their AI capabilities to support a wider range of road conditions. Traditional auto manufacturers are also looking to improve their capability in this space through investment and research to better compete with disruptors like Tesla.
The common pattern and considerable weakness with these industries are their past reliance on large numbers of staff to scale. AI brings the ability to scale organizations and their capabilities, without adding the number of employees previously required. This provides better price points for services, but also allows organizations to better focus their staff’s intellectual capability on handling exceptions, and automating repetitive and error prone tasks.
AI enables organizations to provide higher quality products, at a lower cost that improves over time as data sets grow. AI is an empowering capability for any organization as they compete in a world where every industry is becoming digital.