Generative Artificial Intelligence (AI), which was initially met with both skepticism and awe when it was first introduced to the public, has since grown to be a crucial component of the business landscape. Sectors such as healthcare and hospitality have embraced this cutting-edge technology and invested significant resources in exploring more applications of AI to make their operations more productive and profitable. With 2023 coming to an end and everyone trying to start again, generative AI and its expanding range of uses are important priority for every industry.
How Gen AI and our GenNext will coexist
Renewable energy sources can be more efficient with the help of Gen AI: In order to reduce greenhouse gas emissions and combat the impacts of global warming, solar and wind power are essential. The expensive installation and upkeep expenses of these alternative energy systems continue to be a problem, though. We can now move on to the interesting section, where generative AI comes in handy. Generative AI can increase the efficiency of renewable energy plants by automating the design process. The technology can provide new designs that are more efficient and economical by using machine learning algorithms to evaluate data on energy output and consumption.
Learning assistant and time-saver: Generative AI is a great resource for the e-learning sector, working well in tandem with human staff. Digital learning systems are projected to undergo a revolution thanks to their context-specific responses to focused inquiries, word-image association, and Natural Language Processing (NLP) capabilities. The traditional methods used to create learning materials are frequently labor- and time-intensive, which is a big drawback in professional settings where employees have to quickly become comfortable with new tools and technology. Therefore, the numerous hours that are usually wasted in the process can be avoided by incorporating generative AI into the creation of study materials. Its NLP capabilities have already proven advantageous to the retail sector, where generative AI has been applied, among other things, to the creation of product descriptions. As generative AI becomes more widely used as a training tool for creating study guides and briefing papers, more sectors are probably going to use it.
Software testing with applied creativity: By 2024, the software industry stands to benefit the most from generative AI. Of all industries, this is the case. In particular, generative AI will save time and resources while increasing testing efficiency. Software testing has changed throughout time, moving from manual to scripted automation and data-driven artificial intelligence testing; yet, each of these methods has drawbacks. However, generative AI has the potential to completely transform the software testing procedure. Its capacity to independently pinpoint flaws and generate unforeseen scenarios for a more thorough evaluation of a software’s capabilities is revolutionary. Generative AI is a valuable tool in the software business because of its capacity to test software creatively.
Using Cloud Nine: Native or Hybrid? Even though using cloud technology has many benefits in terms of computing efficiency, there are often significant environmental costs associated with it. It can be the enormous amounts of land needed for server farms or the enormous amounts of electricity needed to keep them operational. Using cloud-based technologies requires spending money on several resources, in addition to the heat that the IT infrastructure produces. Leading cloud providers are working together to lower carbon emissions at server farms, though, as they are aware of the environmental impact. They are collaborating for a greener future in the same way that they have done to protect data from hackers. However, cloud providers do emphasize that without them, sustainable IT solutions are not feasible.
Cloud providers will most likely encourage the faster adoption of low-code and no-code platforms at the software suite level throughout 2024, which will allow the IT industry to deploy “greener” applications. Networked clouds will become a more viable solution as low-code and no-code platforms become more widely used. Moreover, employing sustainable architectures in the creation of networked clouds is expected to raise the efficiency quotient and lower the energy usage at server farms. By providing customers with a vendor-agnostic platform, cloud providers can use yet another cutting-edge strategy to lessen their carbon footprint. Beyond creating a system that can be adjusted as and when “greener” solutions become available in the future, cloud providers will be able to evaluate performance using dynamic metrics by guaranteeing that there is no “technology lock-in.”
Technology is facilitating a grassroots revolution: A recent Deloitte analysis projects that by 2027, the value of “smart” agriculture, which is currently valued at about USD 11.45 billion, would have increased to USD 30 billion. Technological developments will continue to propel agricultural productivity in the near future—let’s assume in 2024. While edge computing, smart sensors, and Internet of Things (IoT) devices are already commonplace on farms, digital transformation technologies can help create a more welcoming ecosystem for farmers and agriculture-related businesses. The implementation of the “Digital Real-Time Analyst,” for example, can assist all parties involved in the agriculture system in locating and obtaining aid in a timely manner. When contact or customer service centers are understaffed, digital real-time analysts can provide crucial support to individuals working at the local level.
Digital Twinning in Agriculture: The “Digital Twin” is one specific innovative technology that has the potential to completely change the agricultural industry. Since there is very little room for error in agricultural processes—mistakes like using the incorrect fertilizer or selecting a crop that isn’t compatible with the soil can leave farmers reeling in losses—digital twin technology can help farmers anticipate and effectively prevent many of these issues. Digital twin technology has a lot of potential applications in agriculture, even though its implementation on farms is still in its early phases. First, in order to evaluate the feasibility of their yield, farmers can use digital twin technologies to provide a “dry run,” although virtually, of their annual cycle. When used in conjunction with cloud and data analytics tools, digital twins can assist farmers in planning ahead and anticipating a variety of scenarios. Because digital twins can be combined with “Big Data” technologies, farmers can benefit from their ability to provide long-term climatic patterns. This allows field workers to plan ahead and protect their produce from harm.
Technology and Therapeutics: By 2024, technology will be used in medicine far more extensively than e-consults and video visits. As software-driven, evidence-based therapeutic interventions for the prevention, management, or treatment of illnesses or diseases take center stage, digital therapies will emerge.
By giving patients the ability to self-manage their symptoms, digital therapeutics (DTx) offers the potential to improve clinical outcomes and quality of life for patients. To urge patients to change their behavior, DTx makes use of digital technology like smartphones, applications, sensors, virtual reality, the Internet of Things, and other tools.
In the future, there will probably be more applications for cloud-powered transformative technologies that are already in use, such edge computing devices and digital twins. However, the need for data-driven digital solutions is expected to rise across the board for businesses, which will in turn spur innovation in the technology sector. Both the public and private sectors, however, are equally likely to invest in technologies that may better ensure the confidentiality of sensitive information as worries about threats to data sovereignty grow. Thus, it is reasonable to anticipate that advancements in cybersecurity will change in the next years. These advancements should allow for greater localization of data storage without increasing costs or energy consumption.
