During IBM’s Q2 results meeting, the company’s CEO, Arvind Krishna, commented that the company has infused AI across its businesses. The hybrid cloud business is no exception to this direction of travel as AI infusion formed the central theme of IBM’s recent briefing on its Hybrid Cloud Managed Services (HCMS). This capability provides application management and cloud operation services and is a separate division from the main consulting arm, Business Transformation Services. HCMS is beginning to demonstrate the assets it is introducing to enable smarter Application Management Services that recognise hidden patterns in data and learns from them in order to continuously improve processes.
Looking beyond Agile and DevOps for app manageability
Speaking from his experience in the EMEA market, Bal Krishnan, Senior Partner and VP, IBM Consulting, set out the patterns IBM is seeing in the market:
Enterprises continue to find themselves struggling with cash and costs because of the ongoing energy crisis, inflation and supply chain disruptions. While some enterprises can improve their top line, others simply cannot – retailers in particular cannot further increase prices. Enterprises are also asking for an angle on sustainability and requesting gen AI benefits in their contracts.
IBM is also seeing the number of vendor consolidation strategies increasing to reduce costs, with sourcing increasingly going in-house for design and management as organizations set up their own captive centres. As the IT landscape evolves, clients and prospects are also looking for full-stack application management, with the focus on managing a business process across multiple clouds. This is increasing the complexity of managed application services, especially as clients need business outcome metrics to verify that quality is improving and that the end user experience is being elevated by the innovation applied to the application estate.
IBM’s response to these trends is to move to an asset-based services model infused with AI (across business and IT) in order to adapt faster to market patterns and client needs.
AIOps-driven AMS
IBM HCMS group focuses on three major offering areas:
- Enterprise Application Services – IBM’s Enterprise Application Managed Services is known for its strength in SAP services, but also has its Oracle practice and its SaaS ISV practice for Microsoft apps, Workday, Salesforce and Adobe.
- Platform Services around cloud choices which is the most highly automated of IBM’s HCMS offerings as it prioritises repeatable, automated and digital worker capabilities for cloud, spanning design and build as well as run and automation.
- Custom and Data Managed Services, which is home to IBM’s original managed application capability and remains its largest AMS area, addressing large legacy and modern home-grown application estates on premises where a significant part of the capability revolves around scalable service integration (SIAM). It also offers custom AMS services on cloud where IBM’s mainframe application expertise is frequently in demand.
Going forward, all these offerings will be underpinned by IBM Consulting Advantage, the company’s AI services platform (https://diginomica.com/how-ibm-consulting-takes-projects-its-gen-ai-platform-ibm-consulting-advantage) which uses MethodX to package Assistants and assets into recipes powered by gen AI. Assets are a mix of tools, products and AI-trained models, while IBM Consulting Assistants are role-based digital assistants to place the hive knowledge of IBM and wider industry into the hands of its 160,000 consultants.
Clearly AIOps has been around for longer than gen AI, and IBM pointed out that the main assets available on IBM Consulting Advantage are not just based on prompt engineering, but are based on a mix of traditional AI and machine learning technologies along with an infusion of gen AI to drive delivery automation and optimization. These assets are now infused with gen AI using WatsonX.
For example, alert de-duplication, event grouping, summarization of tickets root cause, Chatops to look for historic issues, patterns, solutions and available experts for the specific issue and many other use cases. These include assets such as IBM IGNITE Quality Platform for test analysis, planning and execution; IBM PRISM for the automated planning, provisioning and management of workloads on multi-cloud environments; and IBM Consulting AIOps for instrumentation, correlation, prediction and insights. Prompt engineering is applied to these assets to create the IBM Consulting Assistants that help provide data-driven insights for decision-making, based on what information is embedded in each asset. The insights are created from several different points of view, providing developer, security, operations and IT value stream perspectives.
IBM Consulting Advantage does not only work with IBM tools, but will also work with ServiceNow and Microsoft Azure Monitor, for example. If a client requires an on-premises environment, the platform can also be ported to that environment. As clients renew managed application contracts, this AI approach will be embedded in the services IBM delivers.
My take
Intelligent managed application services have been developing for many years, but the real shift for IT service providers is that gen AI can help to quickly share knowledge and experience to help freshly trained consultants work in areas facing stark levels of skills scarcity, as well as support faster problem resolution. It does this by enabling digital assistants that effectively plug the consultant bench into the hive knowledge of the service provider organization. This capability is added to a platform pulling together assets including pre-built libraries of analytic models as well as data sets suitable for training machine learning algorithms as project accelerators.
The addition of gen AI is simply the next stage in evolving a digitally smarter approach to managed application services. IBM’s competitors in this service area such as Accenture and TCS have similar approaches. The more interesting factor here is the enterprise pressure being put on service providers to check a gen AI tick box in the sourcing request, when the more valuable client benefits are actually coming from the assets. These tools are enabled by what is rapidly becoming known as “traditional AI,” an area in which IBM arguably has a stronger pedigree than any other services competitor.
