How AI Machine Learning Is Transforming Business and Technology
With applications across industries, from medicine to marketing to transportation, artificial intelligence (AI) and machine learning have progressed from tech buzzwords to essential business tools. Today, AI machine learning technologies help organizations improve operations, respond to customer expectations, and position themselves as industry leaders.
Consumers and end users have come to expect customized and personalized experiences in both personal and professional spaces, from smart home devices and online shopping to workstations. Increased acceptance of these tailored experiences has driven innovators to rapidly advance the technology.
Latest in AI and Emerging Technologies
AI and machine learning continue to make progress in areas that once seemed far into the future. While major breakthroughs attract attention, incremental advances often have more immediate potential for businesses and consumers.
Advancements in Healthcare and Research
For example, researchers at London’s Moorfields Eye Hospital worked with Google’s DeepMind to develop AI technology capable of identifying more than 50 eye diseases and recommending appropriate referrals.
Google DeepMind also developed AlphaFold, an AI system that can predict the three-dimensional shapes of proteins. Protein structure plays a critical role in biological function. Understanding how proteins fold can help researchers investigate diseases and accelerate scientific discovery.
Since those early breakthroughs, AlphaFold has continued to advance, demonstrating how AI can support scientific research on a much larger scale.
AI & Machine Learning Are Transforming Operations
Businesses across industries are using the data behind AI technology and machine learning to achieve a different goal: improving operations. By gaining insight into behavioral trends and automating administrative processes that traditionally required significant time and manpower, companies can reallocate resources to more impactful and revenue-generating areas.
The potential benefits of AI include:
- Increased productivity
- Reduced operating costs
- Improved speed to market
- Transformed business and operating models
Traditionally, figuring out where to spend time and money to advance business relied heavily on gut instinct and intuition.
With data behind these decisions, organizations can now allocate resources based on what’s actually happening. This makes it possible to accomplish more without necessarily overloading existing staff or recruiting new employees.
These benefits extend beyond theory. In a recent HNM Systems AI staffing solutions case study, a global financial services organization used AI-powered automation and machine learning to improve billing accuracy. HNM’s team helped the organization reduce invoicing errors by more than 85% while recovering millions in at-risk revenue.
Customization Means Happier Customers
Businesses are also using data to learn more about their customers and improve satisfaction. In the Amazon age, customers are accustomed to tracking an order from processing through delivery. These expectations carry over into experiences with other industries as well.
With automation and data insights, customers can receive better communication and faster, more effective responses, especially when things go wrong.
AI-powered customer service tools can help organizations answer routine questions, identify recurring issues, and provide more personalized support. These changes allow companies to focus on building deeper relationships with customers rather than spending so much time putting out fires.
AI doesn’t have to replace human interactions. Instead, it can support customer service professionals by handling repetitive tasks and providing information that helps them resolve more complex issues.
The Security Challenge
The cogs at work behind emerging technologies like AI and machine learning are enormous volumes of data. With the collection and storage of that data, however, comes the growing challenge of data and network security.
How AI Creates New Cybersecurity Risks
Cybercriminals can also use AI technology against businesses. Potential threats include:
- Automating attacks and improving evasion capabilities against detection systems
- Increasing the scale and reach of cyber threats
- Making existing attack tools more harmful and difficult to detect
- Generating more sophisticated phishing attacks using information gathered from websites
As organizations adopt more connected systems, they must also consider how AI affects their security practices.
Using AI to Strengthen Cybersecurity
AI can play a significant role in optimizing the resources needed to stop cyberattacks, much like it improves efficiency in other business operations. Machine learning tools can analyze network activity, identify unusual patterns, and help security teams detect potential threats more quickly.
These capabilities are particularly valuable when organizations manage large networks and cloud environments where manually reviewing every event would be impractical.
For example, HNM Systems helped a global energy and water infrastructure organization strengthen security and reduce manual work through hybrid cloud engineering and infrastructure automation.
Although automation doesn’t eliminate cybersecurity risks, it gives teams more opportunities to identify problems and respond efficiently.
The Opportunity in ICT and Emerging Tech
With so much of business operations happening in the cloud, demand for infrastructure improvements continues to grow. Advances in communications, e-commerce, and AI create extensive opportunities for professionals in information and communications technology (ICT) and emerging technologies.
AI Machine Learning Is Driving Data Center Growth
Behind every AI application is the infrastructure needed to process and store data. As organizations expand their use of AI machine learning technologies, they also need more computing capacity, reliable power, advanced cooling, and high-speed connectivity.
These requirements are driving investment in hyperscale data centers and the networks supporting them. HNM Systems explores this relationship in its recent article, How AI Is Driving the Next Wave of Data Center Growth.
The growth also creates demand for skilled professionals who can design, build, operate, and maintain critical infrastructure. HNM supports these projects through its technology and data center workforce solutions.
In one project, HNM provided technical expertise for hyperscale data center and Network Operations Center (NOC) operations. The engagement supported more than twelve hyperscale locations and helped the client achieve 99.99% uptime.
Building the Infrastructure Behind Emerging Technologies
Both the private and public sectors continue investing in key technologies, especially as smart city technology advances. Government and commercial organizations alike stand to gain from these developments, creating opportunities for growth in ICT and emerging technologies.
As the article The Role of Communication Technologies in Building Future Smart Cities explains, smart cities depend on efficient resource management, connected infrastructure, and technology that improves quality of life.
AI is also increasing the demands placed on the infrastructure supporting everyday business operations. HNM examines these connections in Digital Infrastructure: The Foundation of Modern Business.
Innovations are developing at a rapid pace, and professionals who can help businesses understand, plan, implement, and manage these changes offer immeasurable value. As AI machine learning continues to evolve, organizations will need both the technology and the skilled people capable of putting it to work.
