Top 6 Technology Trends to Watch in 2018

Sridhar Iyengar
Learn more about ManageEngine

Making predictions is always a gamble. But given the way 2017 played out and the way 2018 is shaping up, odds are that the technology trends discussed below will play a significant role in your IT department this year.

Growing use of artificial intelligence, machine learning with data analytics, and business intelligence

Business applications continue to churn out large volumes of data, and users are trying to mine that data to determine patterns and predict user behavior. In ecommerce, users want to know customers' buying patterns, which will help market products better. Website designers want to understand how visitors move through their sites in order to improve conversion rates. And companies want to analyze their sales data to correlate marketing dollars spent with sales dollars generated.

Business intelligence and data analytics activities are becoming easier to perform, and that's driving their adoption in mainstream businesses that are seeking to make better, faster decisions.

Rise of AI-powered chatbots in customer service and support

Over the past few years, chatbots — the automated, human-like chat responders — have been more of an experiment, with limited adoption. Now, chatbots are becoming more mainstream as people see the benefits of those experiments, especially in customer service and support.

AI-powered chatbots are learning how to respond to customers and predict what they want

Unlike human customer service and support reps, chatbots don't have the physical and mental inconsistencies that can degrade service levels. Moreover, AI-powered chatbots are learning how to respond to customers and predict what they want. Based on customer history or questions customers ask during a chat session, AI-powered chatbots can ask users what they need and even ask leading questions, all to improve the support experience.

Use of natural language processing as a new form of human-computer interface

"Star Trek" fans aren't the only ones who've been waiting for this prediction to manifest. Business users, too, are eager to have computers understand natural language.

Take a sales manager who wants to generate a quarterly report. If the manager has to ask for it from an analytics specialist, the manager has to explain what she's looking for and hope the specialist accurately translates her request into something the computer can process in order to generate the information she wants. Natural language processing bypasses the analytics specialist and lets the manager work with a computer directly via speech. In response, the computer may generate a visual or auditory response, depending on the manager's preference.

Tightening of data protection laws

Everything is heading toward digitization. Every business process, every technology, everything done with information — from storing, transmitting and processing it — it's all in digital form. Now, a lot of countries are recognizing that their citizens' personal data needs to be protected.

In addition, they're recognizing that users have to opt-in to these digital relationships, and they have to know the reason their personal data is being provided to a data process or data consumer and know what the consumer will do with their data.

Tighter data protection laws are designed to secure their citizens' privacy as well as prevent data abuse and outright criminal activity such as fraud or theft. The most recent example of this is the European Union's General Data Protection Regulation (GDPR). While some countries like India are also coming up with data protection frameworks, others will enhance their existing framework.

Continuation of cloud adoption in mid-sized and larger enterprises

Cloud is a mindset. Governments and larger enterprises have been slower to adopt that mindset, preferring a private cloud/private data center strategy as a starting point. Now, the biggest barriers to their cloud adoption — security and data privacy risks — are well understood and processes and mechanisms have been put in place to mitigate them. Enterprises now also recognize that most cloud companies invest heavily in the security of their cloud infrastructure, platforms and cloud applications. And they recognize that, in most cases, the security teams of the cloud companies are much larger and much more experienced than their own.

Overall, the larger enterprises are finally becoming comfortable and confident with cloud security and the cloud itself. Governments are also taking the steps to put citizen-facing, non-sensitive data and applications on the cloud.

Use of blockchain in enterprise security for identity management

Blockchain provides a distributed, secure and unique system of records, so you can have a strongly encrypted authentication mechanism that prevents malicious users from breaking in. This makes it a great choice in terms of enterprise security, especially for an identity access management system, which manages user logins and authentication.

In 2018, we'll likely start seeing blockchain adoption in areas such as banking, financial services and healthcare.

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Top 6 Technology Trends to Watch in 2018

Sridhar Iyengar
Learn more about ManageEngine

Making predictions is always a gamble. But given the way 2017 played out and the way 2018 is shaping up, odds are that the technology trends discussed below will play a significant role in your IT department this year.

Growing use of artificial intelligence, machine learning with data analytics, and business intelligence

Business applications continue to churn out large volumes of data, and users are trying to mine that data to determine patterns and predict user behavior. In ecommerce, users want to know customers' buying patterns, which will help market products better. Website designers want to understand how visitors move through their sites in order to improve conversion rates. And companies want to analyze their sales data to correlate marketing dollars spent with sales dollars generated.

Business intelligence and data analytics activities are becoming easier to perform, and that's driving their adoption in mainstream businesses that are seeking to make better, faster decisions.

Rise of AI-powered chatbots in customer service and support

Over the past few years, chatbots — the automated, human-like chat responders — have been more of an experiment, with limited adoption. Now, chatbots are becoming more mainstream as people see the benefits of those experiments, especially in customer service and support.

AI-powered chatbots are learning how to respond to customers and predict what they want

Unlike human customer service and support reps, chatbots don't have the physical and mental inconsistencies that can degrade service levels. Moreover, AI-powered chatbots are learning how to respond to customers and predict what they want. Based on customer history or questions customers ask during a chat session, AI-powered chatbots can ask users what they need and even ask leading questions, all to improve the support experience.

Use of natural language processing as a new form of human-computer interface

"Star Trek" fans aren't the only ones who've been waiting for this prediction to manifest. Business users, too, are eager to have computers understand natural language.

Take a sales manager who wants to generate a quarterly report. If the manager has to ask for it from an analytics specialist, the manager has to explain what she's looking for and hope the specialist accurately translates her request into something the computer can process in order to generate the information she wants. Natural language processing bypasses the analytics specialist and lets the manager work with a computer directly via speech. In response, the computer may generate a visual or auditory response, depending on the manager's preference.

Tightening of data protection laws

Everything is heading toward digitization. Every business process, every technology, everything done with information — from storing, transmitting and processing it — it's all in digital form. Now, a lot of countries are recognizing that their citizens' personal data needs to be protected.

In addition, they're recognizing that users have to opt-in to these digital relationships, and they have to know the reason their personal data is being provided to a data process or data consumer and know what the consumer will do with their data.

Tighter data protection laws are designed to secure their citizens' privacy as well as prevent data abuse and outright criminal activity such as fraud or theft. The most recent example of this is the European Union's General Data Protection Regulation (GDPR). While some countries like India are also coming up with data protection frameworks, others will enhance their existing framework.

Continuation of cloud adoption in mid-sized and larger enterprises

Cloud is a mindset. Governments and larger enterprises have been slower to adopt that mindset, preferring a private cloud/private data center strategy as a starting point. Now, the biggest barriers to their cloud adoption — security and data privacy risks — are well understood and processes and mechanisms have been put in place to mitigate them. Enterprises now also recognize that most cloud companies invest heavily in the security of their cloud infrastructure, platforms and cloud applications. And they recognize that, in most cases, the security teams of the cloud companies are much larger and much more experienced than their own.

Overall, the larger enterprises are finally becoming comfortable and confident with cloud security and the cloud itself. Governments are also taking the steps to put citizen-facing, non-sensitive data and applications on the cloud.

Use of blockchain in enterprise security for identity management

Blockchain provides a distributed, secure and unique system of records, so you can have a strongly encrypted authentication mechanism that prevents malicious users from breaking in. This makes it a great choice in terms of enterprise security, especially for an identity access management system, which manages user logins and authentication.

In 2018, we'll likely start seeing blockchain adoption in areas such as banking, financial services and healthcare.

Related Links

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Observability Is Becoming the Grid That Powers AI - and It Isn't Ready

For fifteen years, observability lived downstream of everything else. Code shipped, something broke, an engineer went to the dashboards. The job was forensic. The pillars we built, such as logs, metrics, and traces, were designed for that role: tell a human what just happened, fast enough that they can make it stop. That role has quietly ended ...

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Move Fast Without the Usual Quality Penalty

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

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The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

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Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...