Originally published on LinkedIn 12/12/2024
As I reflect on the past six months of interactions with associates, clients, and suppliers, a recurring theme emerges: preparedness. This reflection leads me to pose a critical question to client-side executives: Have you proactively asked for the resources necessary to empower your technology to meet future demands?
Over the last few months, I’ve participated in pivotal discussions and observed a significant trend. Many technology teams are not proactively requesting the resources they need to build a foundation for what’s next. What will happen when the board or line-of-business (LOB) leaders demand the deployment of new, critical workloads? Will you and your team be ready to respond from a position of strength when the phone rings?
Mapping the Demand Curve
Across my observations, there are five (or more) critical areas driving technology initiatives on the client side:
- Keep the Lights On (KLO): Managing hotspots, retiring outdated hardware or code, and ensuring ongoing operational stability.
- Technology-Driven Risk and Cyber Controls: Implementing robust measures to safeguard against emerging threats.
- LOB-Driven Growth Initiatives: Focusing on top-line growth, operational efficiency, and innovation.
- Cloud Migration and Hybrid Cloud Strategies: Progressing through phases of cloud adoption to optimize scalability and flexibility.
- Operational Excellence: Encompassing CMDB tuning, service desk model evolution, automation, infrastructure as code, agile transformation, and MTTR reduction through enhanced visibility.
Within these domains, innovation continues to thrive—but so does complexity.
Key Challenges competing for resources: Financial and Work Capacity
I hear and see Teams are navigating several pressing concerns:
- OPEX Pressures including : Escalating operational expenses driven by cloud consumption, Software Licensing Costs: SaaS licensing fees.
- CAPEX Limitations: Barely covering the demands from the critical areas above.
- Aging Assets: The limits of “asset sweating” are being reached, with patching and EOL/EOS waves looming.
- Backlogs and Capacity: Agile backlogs and talent capacity are stretched thin, nearing breaking points as new demands emerge.
- Cyber and Risk Compliance: Meeting growing requirements for technology-based controls.
In light of these challenges, the ability to prepare for hybrid and on-premises AI workloads—and to support them at scale—becomes a pivotal concern and may not be put at the front of the queue...
Preparing for What’s Next
If you’re not proactively proposing structured, executive-level requests for resources, you risk falling behind or worse when the call comes to deploy AI Applications and Workloads. When the demand for hosting critical AI workloads arises, delays in time-to-market could significantly hinder your organization’s competitive edge, and your personal growth in your position.
Written, pro-active cases that will probably surprise senior management are justified right now based on the level of disruption driven by LLM, Decision Support, and other AI workloads.
Consider these critical steps:
- Anticipate Needs: Review data scientist and LOB application requirements for the next 24 months.
- Look at the Competitive Landscape, both in traditional competitors and up and coming disrupters in your firms market space.
- Plan for AI: Design a strawman architecture for AI workloads, including disaster recovery and business recovery plans.
- Network Design: Develop a high-level network architecture that extends from AI pods to stakeholder footprints.
- Evaluate Facilities: Assess power, cooling, and capacity in existing hosting environments.
- Optimize App Generations: Survey and document multiple generations of Apps running in your hosting infrastructure and include plans to decommission outdated applications to reclaim capacity and include the risk and benefits as well as timing potential.
- Review Operating Models and Ways of Working: Do current teams take on new workloads and tech, do you need new ones, do you have the leadership or need to hire, what can you out-task? What costs will be incurred, what are the retention risks with change?
- Upskill Teams: Define enablement and training paths for technical teams and partner ecosystems to support AI workloads.
- Analyze Cloud AI Usage: Evaluate current AI usage in the cloud, considering cost and risk profiles.
- Partner with Security and Risk, Review Cyber Policies: Ensure data privacy, protection, sovereignty, and AI guardrails are robust. Partner to evaluate needs for on and of prem data security , recovery, and vaulting requirements and scenarios.
- Execute RFIs: Structure and execute RFIs to gather data on costs and market capabilities including Cloud, Colo, and On Prem Hosting options and combinations
Building the Business Case
With these steps completed, develop a data-driven business case. Present an executive-level proposal tied to critical business drivers, ROI, and a time-to-market plan. This proactive approach ensures that your organization can meet future demands with agility and confidence.
In a rapidly evolving landscape, waiting to act is not an option. Position your team for success by securing the resources and capabilities needed to embrace what’s next—including the disruptive potential of AI workloads. Bundle the cost of not just replacing EOL EOS Assets but also rearchitecting to support the new Tech, including operations and Cyber.
Do it Now
The time to propose significant uplifts in support of AI initiatives is now, with high visibility to management.
Don't waste a good crisis, this may be the path to funding a much needed uplift to the entire infrastructure that is moving toward hitting the risk register with End of Support dates looming or capacity barriers from factors outside of AI Workloads.
A negotiated plan with LOB's and Senior Management following a proactive well thought out ask may not get everything in place, but will assure your personal and professional positioning for you and your teams maintains relevance.
A lack of proactive asks puts everyone at risk, a rejected plan or compromised plan, even an accepted and funded plan puts everyone in a better place to leverage what's coming very fast.
