What's Ahead for the Software Testing Industry in 2018?

Sven Hammar
Learn more about Apica

As we enter 2018, businesses are busy anticipating what the new year will bring in terms of industry developments, growing trends, and hidden surprises. In 2017, the increased use of automation within testing teams (where Agile development boosted speed of release), led to QA becoming much more embedded within development teams than would have been the case a few years ago. As a result, proper software testing and monitoring assumes ever greater importance.

The natural question is – what next? Here are some of the changes we believe will happen within our industry in 2018:

AI Breakthroughs Will Begin

Organizations will make breakthroughs with machine learning and artificial intelligence in 2018, especially when it comes to using this technology to get a better understanding of their collected data.

Often, it's hard to see the physical manifestation of wider concepts like AI, but in our space, physical objects – “intelligent things” – fill that gap. Previously, IoT devices sent data for limited onward processing; now, machine learning means devices are capable of transforming that same data into actionable insight. Realtime feedback will change the behavior of our IoT devices for good.

Focus on Quality, Security and Resilience

Businesses will need to address the overall quality of their services as the competitive landscape evens out

Given the high level of major outages in 2017, it is evident that the industry has not been moving fast enough to address the explosive growth of the IoT and API economy. There are organizations that are leading the way and achieving great things in both testing and monitoring; however, most are still disproportionally focusing on speed rather than quality, security and resilience.

Looking into 2018, businesses will need to address the overall quality of their services as the competitive landscape evens out. This will result in a refocus on the monitoring of the customer experience and the need for extensive end-to-end testing, embedded within the delivery lifecycle.

Services Will be a Key Differentiator

In 2018, services will become more of the differentiating factor, as capabilities become more similar. Differentiation of services will come down to availability, ease of use and consistency of a quality experience.

The increased reliance on IoT devices, their data and their management will also drive the need for high availability of the API services that these devices will talk to. Monitoring the availability of these APIs will be the critical factor in ensuring that business can continue to run (especially in the manufacturing space), and that business intelligence data can be trusted by decision makers.

Customer Experience Will Become More Important Than Ever

Software testing and monitoring has historically been the realm of the IT team, be that the development teams for testing, or operations on the monitoring side.

In 2018, the digital transformation drive is underway in most enterprises, combined with the explosion of IoT devices and the data processing that derives from them. This will draw the focus onto both the quality of the application and the overall customer experience.

Consequently, both testing and monitoring should be of significant interest to the Chief Operating Officer and the Chief Marketing Officer within organizations, resulting in more rounded testing with team members coming from different parts of the business. That's a potential step change in the type of testing that would be carried out, as well as in the visibility within the business of monitoring results and testing success.

The Way We Validate Results Will Change

2018 will see the adoption of AI, in the form of machine learning, by major software vendors who will be embedding it within their core applications. This machine learning will also become a standard platform for data analytics for new development initiatives. The IoT market will take greatest advantage from this adoption, as the volume of data needing analysis grows exponentially.

This is going to challenge the testing community as new ways of testing and validating the results from AI need to be identified and embedded within the development lifecycle.

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What's Ahead for the Software Testing Industry in 2018?

Sven Hammar
Learn more about Apica

As we enter 2018, businesses are busy anticipating what the new year will bring in terms of industry developments, growing trends, and hidden surprises. In 2017, the increased use of automation within testing teams (where Agile development boosted speed of release), led to QA becoming much more embedded within development teams than would have been the case a few years ago. As a result, proper software testing and monitoring assumes ever greater importance.

The natural question is – what next? Here are some of the changes we believe will happen within our industry in 2018:

AI Breakthroughs Will Begin

Organizations will make breakthroughs with machine learning and artificial intelligence in 2018, especially when it comes to using this technology to get a better understanding of their collected data.

Often, it's hard to see the physical manifestation of wider concepts like AI, but in our space, physical objects – “intelligent things” – fill that gap. Previously, IoT devices sent data for limited onward processing; now, machine learning means devices are capable of transforming that same data into actionable insight. Realtime feedback will change the behavior of our IoT devices for good.

Focus on Quality, Security and Resilience

Businesses will need to address the overall quality of their services as the competitive landscape evens out

Given the high level of major outages in 2017, it is evident that the industry has not been moving fast enough to address the explosive growth of the IoT and API economy. There are organizations that are leading the way and achieving great things in both testing and monitoring; however, most are still disproportionally focusing on speed rather than quality, security and resilience.

Looking into 2018, businesses will need to address the overall quality of their services as the competitive landscape evens out. This will result in a refocus on the monitoring of the customer experience and the need for extensive end-to-end testing, embedded within the delivery lifecycle.

Services Will be a Key Differentiator

In 2018, services will become more of the differentiating factor, as capabilities become more similar. Differentiation of services will come down to availability, ease of use and consistency of a quality experience.

The increased reliance on IoT devices, their data and their management will also drive the need for high availability of the API services that these devices will talk to. Monitoring the availability of these APIs will be the critical factor in ensuring that business can continue to run (especially in the manufacturing space), and that business intelligence data can be trusted by decision makers.

Customer Experience Will Become More Important Than Ever

Software testing and monitoring has historically been the realm of the IT team, be that the development teams for testing, or operations on the monitoring side.

In 2018, the digital transformation drive is underway in most enterprises, combined with the explosion of IoT devices and the data processing that derives from them. This will draw the focus onto both the quality of the application and the overall customer experience.

Consequently, both testing and monitoring should be of significant interest to the Chief Operating Officer and the Chief Marketing Officer within organizations, resulting in more rounded testing with team members coming from different parts of the business. That's a potential step change in the type of testing that would be carried out, as well as in the visibility within the business of monitoring results and testing success.

The Way We Validate Results Will Change

2018 will see the adoption of AI, in the form of machine learning, by major software vendors who will be embedding it within their core applications. This machine learning will also become a standard platform for data analytics for new development initiatives. The IoT market will take greatest advantage from this adoption, as the volume of data needing analysis grows exponentially.

This is going to challenge the testing community as new ways of testing and validating the results from AI need to be identified and embedded within the development lifecycle.

Related Links

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When Automating Forever Becomes Faster Than Doing It Once

People want to be doing more engaging work, yet their day often gets overrun by addressing urgent IT tickets. But thanks to advances in AI "vibe coding," where a user describes what they want in plain English and the AI turns it into working code, IT teams can automate ticketing workflows and offload much of that work. Password resets that used to take 5 minutes per request now get resolved automatically ...

Smarter Systems for Disinformation: How Data-Centric Design Could Transform Online Trust

Governments and social platforms face an escalating challenge: hyperrealistic synthetic media now spreads faster than legacy moderation systems can react. From pandemic-related conspiracies to manipulated election content, disinformation has moved beyond "false text" into the realm of convincing audiovisual deception ...

The 5 Pillars of Cross-Platform Observability

Traditional monitoring often stops at uptime and server health without any integrated insights. Cross-platform observability covers not just infrastructure telemetry but also client-side behavior, distributed service interactions, and the contextual data that connects them. Emerging technologies like OpenTelemetry, eBPF, and AI-driven anomaly detection have made this vision more achievable, but only if organizations ground their observability strategy in well-defined pillars. Here are the five foundational pillars of cross-platform observability that modern engineering teams should focus on for seamless platform performance ...

What's Blocking Scalable AI?

For all the attention AI receives in corporate slide decks and strategic roadmaps, many businesses are struggling to translate that ambition into something that holds up at scale. At least, that's the picture that emerged from a recent Forrester study commissioned by Tines ...

Not All Networks Are Built for the Edge

From smart factories and autonomous vehicles to real-time analytics and intelligent building systems, the demand for instant, local data processing is exploding. To meet these needs, organizations are leaning into edge computing. The promise? Faster performance, reduced latency and less strain on centralized infrastructure. But there's a catch: Not every network is ready to support edge deployments ...

Why Observability Is the Missing Piece in Your Business Growth

Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

Gartner: Regular AI System Assessments Triple the Likelihood of High GenAI Value

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

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The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...