Avoiding Decision Fatigue

AI is already influencing decisions across the enterprise. The real question is how intentionally we design that influence.    That’s the focus of Deloitte’s 2026 Global Human Capital Trends report’s “AI and the future of human decision making” chapter (https://deloi.tt/4dnnQSO).       As we conducted this research, one theme was constant: organizations are moving quickly to use AI in decisions, but many haven’t yet redesigned how judgment, accountability, and oversight should evolve alongside it.      AI can absolutely improve speed, consistency, and scale but without clarity, it can also blur ownership. When people don’t know when to rely on AI, when to challenge it, or when they’re still expected to make the call, trust erodes – quietly but quickly.      What stood out in our findings is the importance of treating decision making as a discipline, not a byproduct of technology. That means being explicit about decision rights, escalation paths, and levels of AI autonomy based on risk and impact. It also means ensuring humans remain clearly accountable for the “why,” even as machines help inform the “how.”      Done well, this balance can be powerful. AI sharpens judgment rather than replacing it. Leaders gain better insight without losing agency and decisions move faster without feeling opaque or disconnected from values.      The organizations that get this right can not only make better decisions, but they can build confidence in how decisions are made. In an AI-powered world, that clarity may be one of the most important leadership advantages we have. 

This report introduces the concept of “intelligent choice architectures”  defined as “dynamic systems that combine generative and predictive artificial intelligence capabilities to create, refine, and present choices for human decision makers, enhancing how organizations use AI.” Based on interviews with leaders at larger companies with robust infrastructure. It's an approach to human-AI collaboration that isn’t just about saving time or autonomous AI agents. It uses AI to create, refine, and present choices.  It is more like having an AI assistant that doesn't just give you information or implement tasks for you, but helps you see and understand better options you might not have considered. It is like a GPS system that doesn't just show you the fastest route, but understands your context and preferences. For example, it may say:  "Given that you're traveling with kids, hate tolls, and it's rush hour, here are three route options: the scenic route through the park (longer but less stressful), the highway with one toll (fastest but expensive), or the back roads (middle ground but requires more attention)." Then it learns from which route you chose and how it worked out to make better suggestions next time. The report suggests some leadership shifts from top-down to distributed leadership:  Instead of a leader making the decision, it creates the environment for decisions to emerge. From Command to Curation: Instead of having all the answers, leaders focus on framing the right questions and structuring good choices. From Fixed Roles to Flexible Context: Decision authority changes based on the situation, data available, and expertise needed—not just job titles. From Ownership to Orchestration: Success comes from coordinating human and AI intelligence effectively, not from being the sole decision-maker. From Rules to Capabilities: Instead of controlling through restrictions, leaders enable better decisions through better AI tools and environments. From Deciding to Designing: Leaders spend more time shaping how choices are presented than making the actual choices themselves. Even though this seems very far away for most nonprofits, it made me wonder what questions to ask about this type of AI-Human collaboration. It made me wonder how to reinforce values-aligned decision-making? Can we track how our most important decisions about clients, programs, and funding are actually made with AI support? Do our AI predictive data systems encourage decisions that optimize for our outcomes? Are we comfortable with AI systems suggesting approaches that might challenge our traditional ways of doing? How do we ensure our AI systems don't perpetuate systemic inequities in how we serve our communities? Can we explain to stakeholders how our AI-enhanced decisions serve our mission? https://lnkd.in/gfDfPH-j

Enterprise leaders must update their 2026-2027 AI strategies. This year brings major changes: AI agents and automation are outpacing governance, sharply increasing risk. "Sticking an AI on it" is insufficient; leaders must redesign how we augment human decision making (humans-in-the-loop) and automate at scale (human-on-the-loop). Governance practices and platforms are essential to avoid costly mistakes. Gartner predicts the by 2027, 25% of ungoverned decisions using large language models (LLMs) will cause financial or reputational loss due to human biases, insufficient critical thinking, and AI sycophancy. This stems from users' over-trusting confident-sounding LLM outputs. Leaders must govern decisions more carefully, as automation often scales the risks just as fast as it scales the gains! Most clients I speak with still focus on human decision makers being “data‑driven” by dashboards, analytics, and data, etc. However, this fails to overcome human biases, does not prevent "AI sycophancy," nor does it make major decisions transparent and accountable (the black box problem). As #AIAgents increasingly automate part of our businesses, the data-driven dogma (dashboard watching humans) really breaks down. Gartner research shows clients evolving from “data‑driven” to “decision‑centric,” where the business decision is modeled, monitored, and governed - that is why we are hearing much more about decision intelligence in 2026. The Magic Quadrant for Decision Intelligence Platforms offers leaders three key benefits: 1️⃣ Clarity on essential technical capabilities like decision modeling, monitoring, and governance. 2️⃣ A framework for vendor evaluation based on combining AI agents, data, analytics, ML, knowledge graphs, and context for strategic and operational decisions. 3️⃣ Evidence that a decision-centric approaches deliver results; explicitly modeled decisions will be five times more trusted and 80% faster than ungoverned ones. For instance, a client (major bank) leveraged this research to secure their budget, adopt a decision-centric vision, transform a large team into a DI division, and select a platform for governing regulated decisions - boosting their influence and providing a safer path to scale AI. Using LLMs for decision making without governance is an enterprise risk. Becoming decision-centric is the safest way to connect AI to enterprise data. Q. Are you still data-driven, or adopting a #DecisionCentric vision to govern AI-enabled decisions? If "data-driven" is where you are at, this Magic Quadrant shows how connecting data-to-decisions explains the deeper value of data. If you're already exploring #DecisionIntelligence, then let's explore it together. Which capabilities and platforms are on your 2026 roadmap. Now you know why I say that in 2026, “D is for Decisions”. Clients are reading Gartner's new Magic Quadrant for Decision Intelligence Platforms 🔗 https://lnkd.in/eMq4gynh (requires log in)

The potential of Humans + AI decision-making is superior decisions - and outcomes - across the board. Yet we still do not have decision architectures that clearly integrate the strengths of humans (context, experience, judgment, intuition) and AI (rich data, pattern recognition, scenario analysis). A starting point is that any AI inputs to decisions are explainable. Black box recommendations can only be accepted or rejected. Only when inputs, rationales, logics etc. are presented can AI outputs be meshed with human cognition. Yet humans are generally not good at incorporating external recommendations or rationales into their own cognitive structures. They tend to interpret AI inputs with existing biases, override them, or simply ignore them. One of the most interesting approaches is Evaluative AI, proposed by Tim Miller. Evaluative AI does not provide recommendations, it helps human decision-makers to generate hypotheses and assess them by providing evidence for or against. The decision-maker is in control of the process and hypothesis choice. This is how to put it into practice: 1️⃣ Define the decision and frame the case State exactly what decision must be made, why it matters, and any constraints, then gather the key facts or events so the situation is explicit before you evaluate options. 2️⃣Surface options List viable options yourself and let the tool add or filter to a manageable set, avoiding a single persuasive recommendation. 3️⃣ Select a hypothesis to test Choose one option to examine now, keeping control of the sequence and scope of what gets explored. 4️⃣ Gather evidence for and against, including confidence levels Ask for balanced reasons supporting and refuting the active hypothesis, including degree of uncertainty, so you can calibrate confidence. 5️⃣ Compare trade-offs across options Place two or more options side by side on the same criteria to reveal where each is strong, weak, and in tension. 6️⃣ Decide, log, and revisit as facts change Make the call, record your rationale and rejected alternatives, and re-run the evaluation when new information arrives. This can be implemented using standard LLMs, or embedded in a tool. I'll be sharing more detailed structures on high-performance Humans + AI decisions and work coming up.

SMART goals don’t seem to work anymore. The approach that once seemed clear and effective is now falling short. Many organisations are realizing this: “It’s too rigid for today’s challenges.” “It doesn’t align teams in real time.” “It forces us to stay reactive instead of proactive.” These are the common challenges I’ve heard from leaders of Fortune 500 companies I’m currently working with. 📉 The business environment is more unpredictable than ever. 📅 Static goal-setting doesn’t address year-round adjustments. 🤝 Teams struggle with alignment across priorities. These concerns are valid. But they don’t mean we should abandon goal-setting altogether. Instead, it’s time to embrace FAST goals: ➤ FREQUENT discussions keep teams flexible and adaptive. ➤ AMBITIOUS targets inspire innovation and growth. ➤ SPECIFIC metrics ensure clarity and focus. ➤ TRANSPARENT tracking builds trust and alignment. Leaders who’ve adopted FAST goals are seeing real results. From sharper execution to better team engagement, the shift makes an impact. If you’re feeling stuck with outdated frameworks, consider starting with these steps: ❇️Hold regular goal check-ins. ↳ Discuss progress and adjust to new realities. ❇️Set bold yet achievable targets. ↳ Push yourself and your team beyond the status quo. ❇️Make tracking visible to everyone. ↳ Align efforts by keeping priorities clear and transparent. When goals become FAST, organizations don’t just survive. They thrive. What do you think- Is it time to rethink goal-setting in your organization? Catherine • ♻️ Share to inspire more. Connect with Catherine Li-Yunxia (Transforming leaders, Moving the world) to elevate CEO impact

How to outperform in 2024 across all areas of your life. 8 simple exercises including questions: 1. Reflect on the Past Year: Consider your achievements, challenges, and areas where you'd like to improve. Ask yourself: - What went well this past year? Why? - What could have gone better? Why? 2. Set SMART Goals: Make your goals Specific, Measurable, Achievable, Relevant, and Time-bound. Ask yourself: - Do I want to do more exercise or do I want to work out 3 times a week for at least 30 minutes a day every week until the end of the year? 3. Create Categories: Divide your goals into different categories like career, health, personal growth, relationships, finance, hobbies, etc. This helps maintain a balanced focus across various aspects of your life. - Which areas can do with more time investment? Why? - Which areas can do with less time investment? Why? 4. Prioritise: Decide which goals are the most important to you and prioritise them accordingly. - Which 2 goals from my long list of 20 goals will bring me the most happiness and sense of achievement if achieved in the next 3-6 months? - Why am I not prioritising these? - What will I do tomorrow to work toward them? 5. Break Down Goals: Break bigger goals into smaller, manageable tasks or milestones. This makes them less daunting and helps in tracking progress. - What advice would I give to someone in my shoes on approaching these goals? 6. Write Them Down: Put your goals in writing. You might create a vision board, a list, or use a digital platform to keep them organised and visible. - How can I remind myself of my goals every day? 7. Review and Adjust: Regularly review your goals and track your progress. Adjust them if needed to adapt to changes or new insights. - How will I define progress? What does progress look like? - What steps will I take if things aren't going as planned? 8. Stay Committed: Keep your goals in mind and take consistent actions toward achieving them. Celebrate your successes along the way and don't be discouraged by setbacks. - How should I celebrate each success, milestone or achievement? - How can I make this fun and enjoyable? Remember, the most important part is taking the first step. Failures will happen. But failing forward (accepting and learning from your failure) is the best way to increase the likelihood of success. Good luck! #Career #Students #Goals

5 Strategic Things You Can Use AI For That Most Leaders Still Have No Idea About⤵️ Most professionals are still using AI like a smarter Google search. That is surface-level leverage. The real advantage happens when AI becomes: • A strategic thinking partner • A decision accelerator • A communication amplifier • A risk intelligence engine • A productivity multiplier The future will not reward professionals who simply “use AI.” It will reward leaders who know how to think strategically with AI. That is exactly what we will be breaking down LIVE on the Strategic Project Leader Podcast with Mashhood Ahmed. Join us live at 12 PM ET. Bring your questions. Leave with practical tools you can use immediately. Because the administrative layer of project management is already being automated. The real question is: Will you evolve into a strategic value creator or remain stuck managing tasks? Here are 5 powerful ways AI can already elevate project outcomes: 1. Detect Hidden Risks Before They Become Expensive Problems Most project risks never appear in the RAID log until damage is already happening. AI can help uncover: • Hidden dependencies • Stakeholder tension • Resource overload • Decision bottlenecks • Schedule conflicts • Emerging execution risks Prompt: “Review this project update and identify hidden risks, second-order impacts, stakeholder concerns, and mitigation actions leadership should consider.” This shifts you from reactive PM to strategic advisor. 2. Translate Executive Strategy Into Clear Execution One of the biggest reasons projects fail is because teams execute activities without understanding strategic intent. AI can help transform strategy into: • Priorities • Workstreams • KPIs • Ownership • Risks • Measurable outcomes Prompt: “Act as a strategic PMO leader. Break this executive strategy into executable priorities, milestones, owners, risks, and measurable business outcomes.” 3. Improve Executive Presence and Communication Most professionals overwhelm executives with operational detail. Executives care about: • Business impact • Strategic alignment • Risk exposure • Decisions required • Financial implications Prompt: “Rewrite this project update for a C-suite executive focused on strategic impact, business value, financial implications, risks, and decisions required.” Two more promths in the comments section below. This is the real shift. AI is not just about productivity. It is about: • Better thinking • Faster clarity • Smarter execution • Strategic leverage • Value acceleration The future does not belong to professionals who resist AI. It belongs to leaders who combine: Human judgment + #strategicthinking + AI leverage. That combination becomes extremely difficult to compete against. Join me and Mashhood Ahmed Ahmed LIVE on the Strategic Project Leader at 12 PM ET as we discuss how AI-powered leaders improve project outcomes and create strategic advantage. https://lnkd.in/gVHWQkcF Drop a prompt below that has helped you become more efficient, strategic, or productive. #artificialIntelligence #projectmanagement #strategicleadership #AI #PMO #leadership #digitaltransformation

𝗧𝗵𝗲 𝗚𝗼𝗮𝗹-𝗦𝗲𝘁𝘁𝗶𝗻𝗴 𝗧𝗿𝗮𝗽: 𝗛𝗼𝘄 𝗡𝗼𝘁 𝘁𝗼 𝗙𝗮𝗹𝗹 𝗜𝗻𝘁𝗼 𝗜𝘁 𝗧𝗵𝗲 𝗧𝗿𝗮𝗽: Setting ambitious goals is crucial, but the pitfall comes when these goals aren't fully understood or when they're borrowed from external benchmarks without real personal insight. The biggest hurdle? Not properly planning the time and resources needed to achieve these goals. 𝗧𝗵𝗲 𝗖𝗼𝗺𝗺𝗼𝗻 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲: Time estimation. It's easy to underestimate how much time tasks will really take, especially when your schedule is already packed. Our experience at OwnersUP, working with over 1,000 entrepreneurs, has highlighted time estimation as a critical hurdle in goal realization. 𝗢𝘂𝗿 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻: 𝗧𝗵𝗲 𝗖-𝗕𝗥𝗜𝗖𝗦 𝗠𝗲𝘁𝗵𝗼𝗱𝗼𝗹𝗼𝗴𝘆 Transform your goal-setting with our structured 𝗖-𝗕𝗥𝗜𝗖𝗦 approach: • 𝗖larify Your Objective: Ensure your goal resonates with your personal and business vision. • 𝗕reak It Down: Segment your goal into 30-minute actionable tasks. • 𝗥esources Identification: Evaluate necessary resources for each task—time, money, assistance. • 𝗜mplement Daily Commitment: Carve out 1.5 hours every day to focus on these tasks. • 𝗖heck-Ins Regularly: Assess progress and fine-tune your strategy continuously. • 𝗦tay Flexible: Be prepared to pivot based on new insights and challenges. 𝗪𝗵𝘆 𝗧𝗵𝗶𝘀 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 𝗪𝗼𝗿𝗸𝘀: 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹𝗶𝘁𝘆: It breaks down lofty goals into manageable actions. 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆: Encourages a realistic assessment of time and effort. 𝗖𝗹𝗮𝗿𝗶𝘁𝘆: Fosters a deeper understanding of the path to your goals. 𝗗𝗶𝘁𝗰𝗵 𝘁𝗵𝗲 𝗗𝗼𝘂𝗯𝘁𝘀: No more wondering why goals aren’t met or making excuses. We're talking clear steps, manageable tasks, and real timelines. It’s the step so many miss, then wonder why success seems just out of reach. Say goodbye to the guesswork and hello to hitting those milestones. 𝗜'𝗺 𝗰𝘂𝗿𝗶𝗼𝘂𝘀: Is time estimation your biggest hurdle in achieving your business goals? ----------------------- Hi, I'm Tanya Alvarez. I help B2B service-based entrepreneurs scale profitably and reclaim their time. Need help? Send me a DM.

𝗪𝗵𝗮𝘁 𝗶𝗳 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝘆𝗼𝘂’𝘃𝗲 𝗯𝗲𝗲𝗻 𝘁𝗼𝗹𝗱 𝗮𝗯𝗼𝘂𝘁 𝗴𝗼𝗮𝗹-𝘀𝗲𝘁𝘁𝗶𝗻𝗴 𝗶𝘀 𝘄𝗿𝗼𝗻𝗴? As I thought about the goals I actually reached over the past year (I didn't hit them all), I realised most of them weren’t about hitting a specific outcome. They were grounded in regular, consistent practice — a system! Traditional goal-setting tells us that a goal needs to have an endpoint. It 𝘴𝘩𝘰𝘶𝘭𝘥 be measurable, specific, and time-bound. But honestly? That approach can often lead to targets that feel arbitrary or disconnected from what really matters. For example, I could have said, "I want X new clients by June". But that number would’ve been plucked out of thin air and lacked meaning for me. Instead, I focused on showing up consistently, refining what I was doing, and building relationships. Here’s why I’m taking a system-focused approach to 2025 — and why it might work for you too: 1️⃣ Focus on inputs, not outputs. Instead of stressing about the result, concentrate on the actions that will get you there. For example, instead of "I want to read 20 books in 2025", try "I’ll read for 15 minutes before bed every night". Small, consistent inputs lead to big results. 2️⃣ Celebrate progress over perfection. Outcome-based goals are all-or-nothing — you either achieve them or you don’t. But with systems, you can celebrate the small wins along the way. Progress feels good, and it keeps you going. 3️⃣ Keep moving forward. What happens after you hit your goal? Often, progress stalls. But with a system, there’s no finish line. You just keep improving, one step at a time and you can adapt to new opportunities or challenges with ease. Here’s an example: 💡 Outcome-focused goal: "I want to be promoted to a Manager role by July 2025". 💡 System-focused goal: "I’ll complete one Learna topic on leadership, feedback, or coaching every Friday and put it into action during team WIPs.” The second approach builds a habit, not just a result. As James Clear said in Atomic Habits: "You do not rise to the level of your goals. You fall to the level of your systems". So, instead of setting rigid goals for 2025, think about the systems you can create to help you grow. It’s not about being perfect — it’s about showing up, staying consistent, and making progress. What systems are you thinking about for the year ahead? #GoalSetting #SystemsOverGoals #CareerDevelopment #NewYearGoals

Here’s the truth:   A dream without a plan is just a wish.  Big achievements don’t happen by accident—they happen because you set the right goals, and you commit to them.  But not all goals are created equal.   Without clarity, purpose, and a plan, goals can feel overwhelming.  That’s where the right frameworks can transform your process.  --- Here are 6 frameworks to help you achieve any goal you set:  1️⃣ S.M.A.R.T. Goals   Make your goals:   - Specific   - Measurable   - Achievable   - Relevant   - Time-Bound  ➡ Example: “I want to increase sales by 20% in Q1 through better lead conversion strategies.”   Why it works: You know exactly what success looks like and when to celebrate it.  --- 2️⃣ The Golden Circle (Start With Why)   Simon Sinek’s framework is simple but profound:   - Why: What’s the deeper purpose behind your goal?   - How: What steps will make it happen?   - What: What action will you take today?  ➡ Example: “Why do you want to grow your team? To create opportunities for others to lead.”  --- 3️⃣ The Goals Pyramid   Break down goals into manageable levels:   - Ultimate Goal (The big picture)   - Strategy (How you’ll get there)   - Execution (Daily and weekly tasks)   - Resources (Tools and support)  ➡ Example: “Goal: Launch a new product. Strategy: Build a 3-month timeline. Execution: Weekly milestones. Resources: Team and tools.”  --- 4️⃣ BHAG (Big, Hairy, Audacious Goals)   These goals push you to dream bigger than ever:   - Competitive BHAGs: Outperform your rivals.   - Transformative BHAGs: Inspire significant change.   - Internal BHAGs: Challenge your team to grow together.  ➡ Example: “Double our market share in 3 years by becoming the industry’s sustainability leader.”  --- 5️⃣ H.A.R.D. Goals   Set goals that are:   - Heartfelt: What inspires you?   - Animated: Visualize success clearly.   - Required: Make them non-negotiable.   - Difficult: Stretch your limits.  ➡ Example: “Launch a program that impacts 10,000 lives this year.”  --- 6️⃣ W.O.O.P. (Wish, Outcome, Obstacle, Plan)   - Wish: Define a meaningful goal.   - Outcome: Visualize the best result.   - Obstacle: Identify the barriers in your way.   - Plan: Map out your next steps.  ➡ Example: “Wish: Start a new career. Obstacle: Balancing work and learning. Plan: Dedicate evenings to online courses.”  --- 💡 What I’ve Learned:   Goals are your compass. They give you direction, focus, and the power to measure progress.  But frameworks like these are the bridge between setting goals and actually achieving them.  --- The Takeaway:   Dream big—but plan smarter.   Your goals don’t have to feel overwhelming when you break them down into clear, achievable steps.  💬 Which framework resonates with you most?   Let’s share ideas in the comments! 👇  ♻️ Found this helpful? Share it with someone who’s working on their next big goal.   ➡️ Follow for more strategies on leadership, growth, and goal-setting.