Delivering quality services at a faster pace and lower cost is certainly on top of the agenda for many business enterprises, and now it has become imperative in the post COVID-19 affected world economy. Leaders looking to get more out of traditional IT operations management should take a holistic approach and bring in new groundbreaking AI technologies to propel customer satisfaction led business growth.
Executives leading managed services functions are all too familiar with the critical challenges of ensuring that their team are:
- Closely observing and maintaining the health of their dynamic IT topography by eliminating blind spots
- Anticipating the failure of applications or infrastructure and assessing its impact on Business
- Facilitating visibility across private/public clouds, and on-premises environments
- Establishing more efficient and stable applications and infrastructure
- Ensuring IT systems are performing at levels necessary to meet compliance and SLA requirements
Most of the well-known players in the Managed Service Provider (MSP) community have connected the dots across the IT landscape and integrated various machine learning capabilities into better algorithmic tools and bots – for a much quicker response and root cause analysis of incidents and events and correlation of data. Moving away from the classic service desk to a service intelligence model can help uncover new opportunities, ensure regulatory compliance, and streamline financial planning.
Service Intelligence – A Digital Transformation
AI combined with other digital technologies such as robotic process automation (RPA), bots and the Internet of things has helped MSPs take a big step towards achieving end-to-end automation. AI identifies a problem, RPA takes machine learning, and bots take action in a sensible way. This technological development is the central element in the design, development, and delivery of new intelligent services. There are several ways in which this intelligence can be applied to transform service operations.
Automating Technical Support Tasks
Service Management organizations which typically spend the biggest proportion of their resources on operational activities - executing service requests, closing incident tickets, delivering changes, etc. - can now leverage AI to intelligently automate complex tasks for making faster, cheaper, and efficient service delivery and thus help their clients achieve their business goals.
AI inevitably improves self-sufficiency and the end-user experience as well as the overall effectiveness of the service desk; wherein the bots provide a near humanlike first level of interaction for the end-users, with a conversation level that is both natural and contextually relevant.
Refocusing Resources
Once an organization successfully uncovers the opportunities using AI in Managed Services, they will be able to indulge in smarter deployment of resources for more proactive and creative work rather than on performing routine, burdensome and repetitive tasks by shortening the cycle for tracking CPU utilization, monitoring backups, managing firewalls, or resolving incidents; thus helping to improve end-user satisfaction with internal or external services.
Enabling Prediction and Auto-Correction Techniques
These service intelligent environments can also achieve 100% availability with their enhanced flexibility, agility, and reliability afforded by uninterrupted monitoring for component failures or usage surges. A predictive and auto-correction model ensures that the system continues to operate without any noticeable drop in performance.
Providing Enhanced Security and Compliance
Last but most importantly, the key benefits of leveraging AI include enhanced security and compliance measures, wherein the machine learning is alert to any drifts in configuration and deviations from baseline performance, which represent potential compliance or security violations.
Encountering Hurdles
Organizations may encounter technical, cultural, financial, or political challenges when looking to embrace AI within their internal service operations. A few we have seen include:
- Legacy issue of old IT infrastructure and systems that are just not ready for an immediate structural change or revamp.
- Hesitance to move forward with AI due to lack of exposure, experience, and training.
- Concern that organization is lacking enough Data Scientists, Analytics, and Subject Matter Experts to interpret the data being churned out and drive business effectively enough to demonstrate significant improvements to the bottom line.
- Lack of adequate budget or scope to embed AI in business processes and upskill or train people for handling their new roles.
- Lack of organizational buy-in.
- Resistance to the idea of letting bots interact with valued customers.
- Concern around future legal or regulatory implications faced if service denial or delay is caused by process automation.
A Path Forward
An MSP which has invested a great deal in AI tools, automation processes, and has trained professional manpower can help organizations take a leap of faith and successfully pilot the journey of uncovering new opportunities or possibilities. When artificial intelligence teams up with managed services, businesses can save operational costs and improve both business stability and efficiency.
If you’re interested in combining artificial intelligence with managed services to trim down costs and boost efficiency, contact us today.
