How will risk and resilience evolve in this bold new future of work?
From education technology to complex organizational digital transformation, I’ve witnessed firsthand how the evolution of new technology has revolutionized the way we learn and respond to our environment.
We are all aware that AI has the potential to completely transform the way we manage risk and build resilience. With this transformation comes a set of challenging questions regarding the realignment of roles, structures, and priorities within our teams.
As business leaders, it is crucial for us to prioritize the following five aspects to effectively scale and thrive amidst the advancements in AI.
1. Simplify, Simplify, Simplify
Do you really need all that complexity? Streamlining your tools is not only a smart move for better engagement, but is also a critical aspect of operating efficiently with AI. Ensuring seamless connectivity and communication between your systems and data is vital for enhancing the quality of work that AI can enhance and generate. By consolidating your tools, you pave the way for AI to deliver its full potential and produce maximum impact for your team.
The first step? Audit your tech stack. You probably don’t need Excel, Powerpoint, and 5 other systems managing your myriad of risks. A big part of tool auditing is ensuring tools can function together in service of a better experience for your team and your customers. How do your tools support a cohesive workflow for business and decision-making teams? Centralizing your knowledge and ensuring connectivity across platforms will give AI the broadest context to drive the most value.
Make sure the apps you have, you really need, and they provide the real-time context, capability, and connectivity your team requires, in a way that fits with the way they work.
2. Manage the Change Journey
It’s easy to get swept up in the hype of AI. Just because something can be automated doesn’t mean it should be. And the more we use AI, the more we need to be intentional about measuring success – with and without the use of the technology.
Conduct A/B testing to track how AI is performing and where you can improve.
If you are not yet experimenting with AI, here are some tests to start with:
- Send 2 communications to your organization – one written by AI, the other written by your team – and track which gets better engagement.
- Ask your team to write a scenario. Ask AI to write a scenario with similar elements. Leverage people and technology insights to bring your scenarios to life in a new way.
- Draft an incident response playbook using AI and do a peer review on the results. Are significant edits required? Can AI reliably generate a baseline set of procedures that can then be adapted as the situation warrants?
As you experiment, leverage regular measurement and feedback reporting to gauge changes in confidence post-simulation, incident response, or as a part of business as usual operations.
By running small experiments, learning from what works, and evolving over time, your team will gain efficiency from AI in a phased approach that doesn’t break decision efficacy or organizational engagement.
3. Shift from Volume to Value
The most exciting aspect of AI is it unlocks our time for higher-value activities, such as strategic decision-making, stakeholder engagement, crisis management, and shaping culture, rather than simple tasks like collecting data or mining reams of documents for insight.
Since these transactional tasks will be commoditized with AI, your risk and resilience team will be defined by your ability to support decision-making and engage your team.
As a leader, your focus will also need to shift away from optimizing routine workflows to enabling engagement. Here are some questions to start thinking through with your leadership team:
How can I unlock the capability and connectivity in my team necessary to resolve complex decision-making?
- How can I escalate issues with the right context?
- How will we enhance connectivity across teams and processes?
- How will we build capability in our team to respond to novel risks and events?
Spend more time on what AI can’t replace.
4. Invent the Future
As with any significant technological advancement, in an AI-augmented world, the work we do will change.
As leaders, we have the opportunity to reimagine what that future looks like for our team.
Build out new career paths.
For your organization to successfully leverage new technology, you will need people to determine when and to what extent to trust AI tools, establishing AI governance and implementing robust QA processes.
Others may be focused on educating the organization on new tools and novel risks.
Still others will be focused on engineering workflows that better engage people inside and outside the organization, supporting better decision-making and agility.
Forge the way and reimagine what your team looks like in this new tomorrow.
5. Empower Everyone
The increased frequency of novel risks and events, shift in responsibilities, and increasing complexity means that the scope of Risk and Resilience will expand into engagement, training and enablement. We’ll see an emergence of teams dedicated to managing high-stakes issues that require thoughtful human attention.
These new roles will focus on delivering a better stakeholder experience through insight, tools, and automation.
Rapidly shifting dynamics mean reevaluating our existing risk and resilience processes to ensure they are in harmony with what the business needs and the way people operate in that context.
Much in the way you perform your technology audit, scrutinize what you are doing from a prioritization, language and process standpoint:
- Priorities: What is ultimately important to your customer? If you were only focused on their priorities, how would that change the way your team operates today?
- Jobs to be Done: Put yourself in the seat of your stakeholder. What tasks are they attempting to accomplish? What questions will they need answered to be able to do their work well? In a perfect world, what would that interaction look like?
- Terminology: Is the language you use to describe your program and its activities accessible and easily understood by those you serve in the business? Do you use terms familiar to non-experts when communicating context or building capability in other teams?
- Connectivity: Where do you have the most traction in your organization? Where have you struggled? What separates the two? How can you solve for the difference?
- Focus: Instead of adding to your team’s priorities, tasks, or process, challenge yourself to simplify first. What would you do if you were designing your team’s practices from scratch, knowing what you know now? What would you take away? What is the simplest way to test these ideas?
This requires a big mindset shift from reactive to proactive; risk, resilience, and crisis teams are so used to firefighting that we don’t step away often enough to consider decision-making in business as usual. Efficiently answering risk-related questions is non-optional in fast-paced change, but helping stakeholders find answers without having to ask is what building a risk-savvy and resilient culture is all about.
A New Era of Learning
Hype or no hype, in this brave new future of work, we’re all learning as we go.
It may feel overwhelming, but it’s an exciting time filled with immense potential.
AI opens up incredible opportunities for your team to engage and empower your organization like never before.
To learn more about how iluminr can help you build a more risk-savvy, resilient, and agile enterprise, visit us at iluminr.io.
Author
Paula Fontana
VP, Global Marketing
iluminr
