Artificial Intelligence (AI) has become a buzzword that symbolizes the future and everything it entails. AI has not only replaced traditional computing technologies but has also altered the way businesses operate. From healthcare and financial systems to research and manufacturing, it has greatly influenced almost every sector. Not everything that is called AI is actually an artificial intelligence, but we are not going to delve into that discussion today.
The information technology industry is all about computers, software, and other data flows. AI can play a significant role in this field. AI is a discipline of computer science aimed at transforming computers into intelligent machines that would otherwise be impossible to achieve without using a human brain. Artificial intelligence assists computers in thinking, whereas computer vision assists them in perceiving and comprehending their environment. Using AI and ML, one can create systems that exhibit intelligent behavior, offer solutions for complex problems, and emulate the human intelligence within machines through algorithms and computer-based training.
The Impact of AI in IT
If developing and deploying IT systems on a big scale seemed unattainable before, it is now possible thanks to AI’s development of powerful algorithmic capabilities. Many fundamental difficulties in IT have been solved and optimized as a result of digital transformation and the industry’s adoption of AI technology.
Developing secure systems
On top of a fully functioning AI system, a data security plan is essential for protecting confidential data such as personal, financial, and other information. Large volumes of consumer and strategic data are stored by the government and corporate companies, which must be kept secure at all times. Using advanced algorithms and machine learning, AI can provide a layer of protection throughout all these systems for ensuring their safety.
Programmers can use AI techniques to help them find and fix software defects and write code. The use of AI in coding generates ideas, improves productivity, and provides bug-free, clean code. In addition to enhancing overall efficiency, the AI system will reduce downtime throughout the manufacturing process by making relevant suggestions based on the code structure.
Increasing efficiency through automation
One of the most significant advantages of automation is that much of the “legwork” can be done with little or no human participation. IT departments can automate back-end procedures and save money by reducing the number of personal hours they spend using deep learning technologies.
When it comes to application deployment control, it’s essential to consider the different stages of software development. As a result, software versioning management is crucial and extremely useful during the development stage. And, because AI is all about foreseeing potential difficulties, it’s become an essential and precious tool for detecting and anticipating troubles at this level. As a result, they can be repaired without causing any significant issues, which means developers won’t have to wait until the app’s final stage to improve its overall performance.
Improvements in quality assurance
During the development cycle, quality assurance is primarily concerned with ensuring that the appropriate tools are employed. In other words, AI techniques can assist software engineers in using proper tools to detect and repair various faults and flaws in apps and adjust them automatically during development.
AI in IT: Should companies implement it?
There are a variety of ways in which organizations can use AI. The overarching intention is to improve the performance of the business. AI, for instance, could be used to generate automatic reminders for departments, teams, and consumers. Also, it can monitor network traffic and perform a variety of dull and repetitive tasks that would otherwise take a lot of time for people to complete. Due to this change, they will have more time and energy to devote to other significant aspects of the business.
Another advantage for businesses considering AI implementation is the individualized customer experience. This will cover everything from product recommendations to answering inquiries and assisting users in finding things. Furthermore, AI enables businesses to combine enormous amounts of data that would otherwise be impossible to merge, resulting in strategic insights.
However, for many businesses, the notion of using AI may appear daunting and foreign. About 38% of executives feel that managers’ lack of understanding of emerging technology is the biggest roadblock to AI implementation in their company. Fortunately, AI will be considerably easier to integrate when teamed with the IT department.
Prediction of AI in the IT Sector
Acquisition activity will expand, and AIOps (artificial intelligence for IT Operations) will migrate closer to the edge as AI-enhanced automation becomes more intelligent and more contextual. Here are the top ten predictions to keep an eye on.
1. Markets for AIOps will keep heating up
This market has seen a lot of growth in the last year, with new entrants and some startup acquisitions. As larger incumbents strive to upgrade their portfolios, M&A activity is likely to continue beyond 2020.
In terms of client adoption and AIOps maturity, there’s still a lot of work to cover. According to a report by 450 Research, only one out of every five businesses has implemented any machine-learning software.
In addition, according to the study, half of the respondents have implemented or plan to install machine-learning software from third parties, such as cloud providers like Amazon Web Services, rather than developing their own AI and machine-learning algorithms. Because of the scarcity of in-house AI talent and the difficulty of developing AI applications, third-party vendor deployment tactics are expected to expand.
2. The use of AIOps will be widespread at the edge
Cloud-based AIOps solutions are standard. However, as data volumes and use cases expand, this is becoming more expensive and slower. As a result, businesses will begin to put AI technologies at the network’s edge.
AI-assisted monitoring will be possible within a few minutes of the data center connecting to the cloud service. There is no longer any time spent traveling between the data center and the cloud service.
Best of all, using AI on edge won’t necessitate learning new skills. Cloud-based deployment takes place invisibly behind the scenes. The benefits of AI to IT operations teams will be solidified by intelligent edge technologies integrated with the intelligent cloud.
3. Privacy concerns will grow
AI on edge makes it increasingly feasible for businesses to monitor end-user devices such as computers, tablets, and smartphones. Security teams have been watching these devices for years, but IT operations have traditionally handled those activities within the data center.
By utilizing AIOps, IT will be able to advise employees on how to take advantage of the apps on their devices. Moreover, it will enable enhanced control and insight into the overall IT environment.
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However, privacy concerns are serious. AIOps will be able to monitor everything that employees do with their devices. As the separation between professional and personal time has blurred, this could mean access to private banking accounts or medical appointments, for example.
In collaboration with legal and human resource departments, IT industry representatives must find the right balance between monitoring devices for employee safety and protecting individual privacy.
4. Business stakeholders will be aligned with AIOps
For years, IT companies have worked to get closer to business stakeholders to understand their needs better. IT operations should be thinking the same way, and AI will help them get there. According to a recent OpsRamp survey, 68% of IT operations leaders believe their mission is to provide agile, responsive, and resilient infrastructure to support fast-changing business requirements. AI will play a part in predicting the impact of business services by assessing infrastructure measurements and connecting them to key performance indicators.
5. DevOps practices will be supported by AIOps
IT operations and ITSM teams are considering DevOps technologies, skills, and procedures to update their processes and keep up with business and market expectations. According to 68% of respondents in the OpsRamp poll, DevOps skills were at the top of the list of required talents.
By automatically improving code for performance, AI can aid DevOps techniques. AI can spot trends that suggest inefficient infrastructure resource usage and even conduct repairs independently. DevOps’ continuous development and integration (CI/CD) cycles might benefit from a more robust and efficient environment.
6. Government investments in AI will lead to more innovation
Foreign countries, such as China, are heavily investing in AI. The same is likely true for offshore cybercriminal groups. As a result of these pressures, government agencies will be more likely to invest in AI and machine learning research for their own criminal and terrorist surveillance programs and other data efforts. For that, premium-quality data labeling for proper model training is crucial. The private sector will benefit from these initiatives, contributing to filling security monitoring and automation gaps.
7. Data enrichment will become more valuable
AI algorithms don’t need a lot of data to run; they only need valuable data. Companies are increasingly looking for easier ways to enhance their data before feeding them to AI algorithms. DataFox, Oracle’s data engine, already incorporates many of these capabilities, making it easier for businesses to access enriched data AI needs to perform well. DataFox makes data enrichment straightforward for enterprises that wish to apply artificial intelligence.
8. AI ethics will remain a contentious issue
Governments are looking into how to police AI when used to create “deep fake” content. Several reports have highlighted that AI reveals serious concerns regarding diversity bias and that companies might choose to rely on white box AI vendors rather than evaluate their own AI usage.
9. AI will make HR more efficient
Recruiting great talent is a vexing problem that both HR and business leaders are concerned about. Too much time is spent sifting through applicants, holding interviews, and following up, with varied outcomes. On the other hand, HR systems with adaptive intelligence capabilities can speed up the process while improving applicant experience and results.
10. Real-time pricing will be a game-changer with AI
Often, companies find it challenging to define their actual costs and ideal pricing for their products and services because supplies, materials, equipment, and other costs vary significantly. When prices grow, profit margins may not be enough to keep the company afloat. Companies may not realize that they have more profit or price freedom when costs decline. AI can track price changes in real-time and assist businesses in adjusting their prices to maximize sales and profit.
The future is impossible to foretell with AIOps, as it is with any cutting-edge technology. However, one thing is for sure: IT and business will continue to demand smart intelligence. Data, tools, and unpredictability are too much for humans to handle without losing considerable productivity, customers, and market potentials.
Artificial intelligence will play a significant role in improving IT operations in the next year. By combining artificial intelligence tools and processes, IT will be able to gauge the health of its infrastructure and services, as well as find probable root causes and solutions quicker to assist the business.
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Photo credit: The feature image has been done by Jordi Calvera.This guest article has been submitted by Melanie Johnson. We appreciate all guest contributions but the opinions expressed by the author do not necessarily reflect the views of TechAcute.