2020 will see AIOps adoption going mainstream, yet there are significant challenges and cautions, which will shape AI's development in not only IT but across business and society.

Start with How AI Will Evolve for IT in 2020 - Part 1

AIOps privacy and security considerations grow

With AI on the edge, companies will more easily monitor desktops, tablets and other end-user devices. AIOps will enable IT to guide employees on improving productivity from the applications installed on their devices while delivering greater visibility and control around the entire IT environment.

Yet there are real privacy implications since these systems can also be a "big brother," watching and reporting on a user's every electronic move. Not only is that an ethical issue but a potential privacy violation, possibly exposing personal banking accounts or medical appointments, for instance. IT leaders, in partnership with legal and HR departments, will need to strike the right balance between monitoring devices for business stability and protecting individual worker privacy.

On the security front, AI can help monitor networks for cyber-criminals and prevent breaches. But those same algorithms could also be used against companies — to assist attackers by creating fake accounts or bypassing anomaly detection systems, for instance. IT will need to improve the security protections in applications and learn how to detect AI attack methods before they hurt the business.

AIOps market solidifies

There's been ample expansion in this market over the past year, with new entrants as well as several acquisitions of startups. M&A activity will probably continue into 2020 as larger incumbents seek to modernize their portfolios.

The AIOps maturity curve is still nascent, however, when it comes to adoption. Just one in five organizations have implemented some form of machine learning software anywhere in their business, according to a study by 451 Research.

The research also showed that 50% of respondents have either deployed or plan to deploy machine learning software from third parties, including cloud providers such as AWS, versus building their own AI and machine learning algorithms.

AI furthers DevOps

IT operations teams are looking at DevOps tools, skills and methods to modernize how they work in tune with business and marketplace demands. In the OpsRamp survey, DevOps skills topped the list of needed capabilities, according to 64% of the respondents.

Artificial intelligence can also help further DevOps practices by automatically optimizing code for performance. AI can discover patterns that indicate inefficient use of infrastructure resources and even make fixes automatically. This can provide a more stable and efficient environment for continuous development and continuous integration (CI/CD) cycles in DevOps.

AI will affect job roles in IT operations

Just as cloud computing created an entirely new set of development and IT skills, AI and ML will drive a similar change in how IT teams upskill. Research shows that AIOps is helping eliminate tedious work and improve results for IT operators. A recent OpsRamp survey found that 77% of organizations said the number of open incident tickets went down after deploying an AI-powered operations system. A majority of respondents also reported the elimination of repetitive tasks across the incident lifecycle and faster root cause analysis and problem resolution. This opens the door for IT operations staff to pursue data science and development skills so they can manage the automation of policies and actions in the AI tools, rather than doing grunt work. Data scientists will play a large role in determining the best recommendations from the AI systems and understanding when to override the suggested actions.

There is much uncertainty about the future of artificial intelligence in our world, much less within IT. AI thought leaders, scientists and architects need to resolve technical issues with developing, training and deploying models along with balancing the many ethical, privacy and dangerous ramifications of ill-designed AI use cases.

One thing's for sure though: the need for smart intelligence in IT and in business will only grow. There's too much data, tools and unpredictable change for humans to handle without risking significant productivity loss, customer defections, and missed market opportunities. In IT Ops, AI has the potential to impel incredible positive change for IT organizations and the people they serve.