Strategic Roles in AI Management

Your Leadership Blueprint for the Future 🔛 If you're an executive grappling with the fast-paced evolution of Tech, AKA #ai, you're far from alone. But while some see a challenge, I see an unprecedented opportunity. #GenerativeAi isn't just the future—it's your next competitive advantage. As someone who has spearheaded major technological integrations at AT&T, embracing AI today is not an option but an imperative. >>Key Leadership Strategies in the AI Era 1. "Active Listening: Your Secret Weapon in AI Adoption" Begin by conducting internal audits or surveys to understand the current perception of AI within your organization. Address concerns openly in town-hall meetings. 2. "AI: Augmenting Human Excellence, Not Replacing It" Implement pilot projects that clearly show how AI can improve but not replace human tasks. 3. "A Vision Well Communicated is a Vision Half Realized" Develop a transparent roadmap for AI adoption and share it across all organizational levels. 4. "Collective Learning: The Cornerstone of AI Success" Organize regular training sessions and encourage cross-functional teams to collaborate on AI projects. 5. "Human Potential: The X Factor in Your AI Strategy" • Celebrate and reward creativity, problem-solving, and other uniquely human skills that AI can't replace. >> Reshaping Corporate Roles for an AI-Driven World • "From Rote to Remarkable: Entry-Level Roles Reimagined" Invest in training programs that allow entry-level employees to upskill and take on more creative or strategic roles. • "Middle Management: Your New Role as the Talent Nurturer" Pivot from task managers to talent developers, focusing on guiding teams to maximize the use of AI tools effectively. • "Senior Leaders: Data-Driven Culture Architects" Lead by example. Utilize AI to make informed decisions and set a precedent for a data-driven culture. >> Organizational Structure: The New Shape of Success • "Flat is the New Up: Why Project-Based Teams are Tomorrow's Winners" Move toward a more agile structure that encourages rapid decision-making and adaptation. • Strategic Partnerships: Your Path to AI Superiority "Don't Just Compete, Dominate: Partner to Innovate" Seek partnerships with AI solution providers or academic institutions to stay ahead of the curve. This tech shift and paradigm change will redefine leadership, organization, and strategy. The AI revolution is already here—how you respond today will determine where you stand tomorrow. Are you leveraging AI to solve real-world problems, or are you still in the exploratory phase? •••••••••••••••••••••••••••••••••••••••••••••• Mariana Saddakni, ★ Digital Product Innovation, Operational Mastery, and Customer Experience Excellence ★ Former Global Head of Product and Customer Experience, AT&T– Fractional Executive, Service Industry Growth and Retention Expert 🌐 Let's connect! ••••••••••••••••••••••••••••••••••••••••••••••

💬Now is the time for leaders to rethink job descriptions. Many believe that updating job descriptions every 3-5 years is sufficient. 🐌 Those days are gone. ⏩ You should be reassessing jobs every 4-6 months. Focus on the human elements that Al cannot replicate: ✅ creativity ✅ strategy ✅ interpersonal skills Then, thoughtfully redesign roles to use Al's strengths so that there’s more time to apply those human elements! This is not about replacing jobs, but reimagining them to foster innovation and drive business growth. What does this practically look like? 🖥️ IT As AI takes over routine coding and troubleshooting tasks, IT professionals can focus on designing complex, strategic IT architectures, cybersecurity innovations, and facilitating the integration of new technologies within the company. 📊 Finance AI can handle data analysis and report generation. Finance experts can shift towards interpreting this data for strategic decision-making, focusing on financial forecasting and advising on investment opportunities leveraging AI-driven insights. 🤝 Sales With AI handling initial customer inquiries and lead qualification, sales representatives can dedicate more time to understanding client needs, building relationships, and developing customized solutions that truly resonate with each customer. 🔄 Operations As AI streamlines logistics and inventory management, operations personnel can concentrate on optimizing supply chain strategy, vendor relations, and sustainability practices. 👥 HR AI can manage payroll, benefits administration, and resume screening. HR professionals can then focus on employee engagement strategies, professional development programs, and fostering company culture. 🎨 Marketing With AI taking on market analysis and targeted advertising, marketers can pivot to crafting more compelling brand narratives, innovative campaign strategies, and engaging content that speaks to human emotions and experiences. ⚖️ Legal AI can assist in document review and due diligence processes. Legal professionals can focus on complex negotiations, strategic counseling, and providing personalized legal advice where human judgment is critical. 📦 Supply Chain AI could handle demand forecasting and inventory optimization. Supply chain experts can then work on strategic partnerships, resilience planning, and exploring new market opportunities. —- The savviest employees have learned new ways of working already. How about you? Have you told anyone that you no longer work the same way? Share how you’re working differently now 👇🏻 #Innovation #Growth #AI #management #FutureOfWork

Your role changes when your AI teammates start working together. Most teams brief each Custom GPT teammate separately and lose context in handoffs. Trailblazing teams connect AI teammates so expertise flows seamlessly from positioning to content to campaigns. One conversation, full context. Harvard research with P&G professionals shows that when people work with AI, "you stop caring as much about the normal boundaries of your job." Connected AI teammates speed up this transformation. Your positioning expert's GPT works directly with your content expert's GPT. Knowledge flows where customers need it, not where org charts say it should. This week's newsletter explores: ► Why most teams get stuck using AI individually instead of as connected systems ► How to build your first AI chain that combines multiple areas of expertise ► The three phases of AI adoption and why Phase 3 transforms your role from doing tasks to strategic work and orchestrating AI systems ► Real examples of teams rethinking work around customer outcomes, not org charts ► How a GPT Navigator helps you pick the right teammates for any project Teams connecting their AI are working differently. They eliminate handoffs instead of managing them while discovering their jobs are evolving in the process. Work is shifting around what customers need, not what our org charts say. Chained GPTs show you what that future looks like. Read the full issue below. There's also a 16-minute AI podcast version in the comments for those who prefer to listen while multitasking. See link in the comments. Huge thanks to Angie Hill (SVP of Growth and Integrated Marketing at Procore Technologies) and Maggie Miller (Senior Director of Corporate Marketing at HackerOne) for sharing how chaining AI teammates is changing their approach to collaboration and strategic work. The infrastructure is here. Will you keep working with AI teammates individually or start chaining them together? Share this with your team and others to inspire them with this vision and approach to transformation.

Will the Chief of Staff role survive the coming wave of AI? There is no doubt that the future of AI will drastically change the workforce. Many roles will become obsolete, and others will dramatically change in nature as they adapt to widespread AI use. In Lawrence Coburn's recent article, he responds to an AI company Chief of Staff's claim that her job will be gone in as little as three years: "There is no role in the modern enterprise, other than perhaps Founder / CEO, that is better suited than Chief of Staff to survive the coming AI wave." And I completely agree with his take… Let's dive into why. *First, here are FOUR TRUTHS about company leadership* 1)   Humans are necessary to implement the strategy, culture, leadership, and operating rhythm for a company, and to navigate the constantly changing highest priorities across an organization. 2)   Executives should be spending their time on vision, growth, strategy, and leadership. 3)   Direct strategic and executional support (the chief of staff role) is critical to executives staying in this “vision space.” 4)   The wide-reaching strategic capability of the Chief of Staff role is both the armor and the toolkit in the Age of AI. *Now, let's talk about AI use* Most practically, the Executive *will not* be the person continuing to identify, learn, use, iterate, or create working guidelines for the many AI platforms that will hit the market over the coming years. They’ll have people for that, as they should (see #2). And the best human for cross-functional companywide strategic projects? The Chief of Staff. *The Chief of Staff role is well-insulated in the coming wave of AI* Chiefs of Staff are highly strategic and have massive, org-wide breadth to the initiatives they take on:  - An arguably perfect yet simple definition of the CoS role is “to tackle major strategic initiatives for the business leader.” Strategic initiatives will never be obsolete. - AI will undoubtedly automate the least-strategic components of the CoS role leaving more time for the impactful work of a Chief of Staff. - As Lawrence illustrates, "Introduce technology that facilitates the staff meeting? No problem, the Chief of Staff will simply invest those returned hours in strategic recruiting, in strategic planning, in stabilizing that VP who has lost faith, in helping close that round of funding." Additionally, human relationships are the cornerstone of the Chief of Staff role. High EQ, understanding of team dynamics, and the mental and emotional makeup of the specific executive a Chief of Staff supports cannot be duplicated. "The Chief of Staff May be the Last Knowledge Worker Standing in the Age of AI." Link to Lawrence's article in the comments. Ps. Does your company have an AI Policy yet? Join us on July 18th for a workshop with Lawrence & Sophie McNaught that will walk us through just how to start. #chiefofstaff #AI #CEO #management #future #innovation #humanresources

Despite AI’s rapid rise since the launch of ChatGPT, only 1 in 4 companies report real business value from Generative AI. Even fewer are ready for what comes next: AI agents that work toward goals instead of following explicit instructions. In my latest article, published in the American Management Association's quarterly journal, I outline a systematic approach to AI implementation that highlights three critical leadership dimensions: 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆: Leaders need to align AI efforts with business goals and KPIs. Start by identifying measurable value drivers, like customer conversion or cost reduction, and assess how AI can support them. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗶𝗻𝗱𝘀𝗲𝘁: AI adoption isn’t a traditional IT rollout. Success requires experimentation, iteration, and tight collaboration between business and tech teams. A clear idea funnel and review checkpoints help avoid sunk costs. 𝗖𝘂𝗹𝘁𝘂𝗿𝗲: AI adoption depends on trust and transparency. Employees often hesitate to admit they use AI tools, fearing judgment. Leaders must set guardrails, encourage experimentation, and design workflows that balance human oversight with AI autonomy. Agentic AI introduces teams of autonomous agents capable of collaborating across departments and even across companies. But realizing this vision takes more than technology. It requires true leadership. How are you preparing yourself to lead as you bring AI into your workplace? Read the full article: https://lnkd.in/dcwsd98h #ArtificialIntelligence #Leadership #IntelligenceBriefing

🔶 Comparison of NIST SP 800-218A and ISO 42001 Organizational Roles🔶 Many of you have been exploring use of NIST SP 800-218A as your Secure Software Development Lifecycle framework (SDLC) for AI systems, which is a totally appropriate strategy. In this process you’ve likely noticed that NIST calls out specific “Audience Roles”, which offer yet another perspective on defining what ISO42001 refers to as “roles with respect to AI systems” (Clause 4.1). Today we'll highlight some of the similarities and differences between these different roles as semantics can make all the difference in the world when building your governance program(s). 1️⃣ NIST SP 800-218A Audience Roles 1. AI Model Producers: Organizations developing their own generative AI and dual-use foundation models. 2. AI System Producers: Organizations developing software that leverages a generative AI or dual-use foundation model. 3. AI System Acquirers: Organizations acquiring a product or service that utilizes one or more AI systems. 2️⃣ ISO 42001 Organizational Roles 1. Producers: Entities responsible for creating AI systems and ensuring they meet specified requirements. 2. Providers/Developers: Individuals or organizations that develop AI technologies and integrate them into systems. 3. Customers/Users: End-users or organizations that use AI systems for various applications, ensuring that their needs and requirements are met. 🅰 Similarities - Producers (ISO) and AI Model Producers/AI System Producers (NIST): Both frameworks emphasize the role of entities responsible for developing and producing AI models and systems. These roles focus on ensuring that AI technologies are built to meet specified requirements and standards. - Providers/Developers (ISO) and AI System Producers (NIST): These roles involve the development and integration of AI technologies into broader systems. They both highlight the importance of secure development practices and the integration of AI models into functional software systems. - Customers/Users (ISO) and AI System Acquirers (NIST): Both roles represent the end-users or organizations that acquire and use AI systems. These roles ensure that the AI systems meet user requirements and are secure, reliable, and compliant with relevant standards. 🅱 Differences - Specificity to AI: NIST SP 800-218A is tailored specifically for AI systems, with roles uniquely defined for AI model and system producers. ISO 42001, while inclusive of AI, addresses a broader range of software development activities. - Role Overlap and Clarity: NIST SP 800-218A roles are distinct in their focus on AI, potentially leading to overlapping responsibilities but with clear distinctions. ISO 42001 roles are broader, encompassing general software development responsibilities, including but not limited to AI. For help getting started, please reach out! A-LIGN #iso42001 #TheBusinessofCompliance #ComplianceAlignedtoYou

⚠️ 170 million new jobs will be created by 2030. (And 92 million will be lost.) → That’s a 22% churn in the global job market According to the latest WEF report. But these new jobs? They won’t look like the ones we know. The AI era isn’t just about automation It’s about reinvention. Here are 20+ AI-powered roles already reshaping the workforce: → Prompt Engineer – designs the inputs that guide AI behavior → AI Risk & Governance Specialist – ensures systems are safe, fair, and aligned → Decision Engineer – builds shared workflows between humans + machines → AI Ethicist – defines the moral boundaries of what AI should do → ML(Ops) Engineer – deploys and monitors machine learning systems → Head of AI – sets the AI vision and strategy for an entire org → Data/AI Translator – bridges business needs with AI solutions → Model Validator – stress-tests AI models for accuracy and bias Some of these barely existed 3 years ago. Now they’re must-haves. 🔁 We’re moving from data → to decisions → to agents. AI isn’t just predicting outcomes. It’s taking action. And that shift? It’s transforming who we hire, how we work, and what we need to learn. The real edge? Not just knowing AI. But knowing how to build it, guide it, and govern itt ogether. Want to future-proof your career? Start here: Learn the language – Understand LLMs, agents, and AI systems Pick a lane – Technical (ML, data, tools) or Strategic (governance, ethics, ops) Build something – Start with ChatGPT, LangChain, HuggingFace, etc. Think beyond tools – Learn decision-making, ethics, and design thinking Stay curious – The fastest learners will lead this wave 👇 This chart is your career cheat sheet. 🔁 Repost to help your network stay ahead ✅ Follow Gabriel Millien for future-ready insights on AI, careers, and transformation

Every CRO needs an AI strategy. Here are five principles to guide your thinking from my article in Selling Power Magazine: 1. Companies will differentiate and win based on proprietary data and workflow integration. It all depends on the quality of the data provided to your AI models and how data is integrated into revenue-specific workflows. 2. Keep your eye on two key outcomes – predictably hitting the company’s revenue number every time and boosting the productivity of revenue-impacting employees. 3. You own the technology stack It is a fundamental CRO responsibility to make revenue-impacting employees as product as they can be, using AI and other tools. You can’t do that unless you take personal responsibility for the tech stack. 4. You don’t have to be an AI expert, but be thoughtful about the workflows you want to improve. Rely on trusted technology partners for AI expertise, while you focus on the actions your teams need to take to drive revenue. 5. Balance human intelligence and AI – while thinking big about new possibilities. AI is so much more than ensuring reps hit their quotas. Think about how you can meaningfully increase the amount of revenue every revenue-impacting employee in the org can generate and support – from reps to execs. The potential gains from employee contributions are too compelling to ignore. Which is why AI strategy should be your number one priority. Thanks for the feature, Selling Power Magazine!

People are stubborn. AI is proving not to be. Imagine a world where we create AI Workspaces of egoless agents who, beyond anything else, self-improve and adjust. These AI Workspaces are not just about automating tasks; it's about creating an ecosystem where AI agents continuously communicate, iterate, and evolve – essentially, a living organism that learns and improves autonomously. A kind of utopic company that had only ever been a matter of imagination for C-suite executives. Here's an example of how it would work: 🎨 Design Phase: An AI designer analyzes trends and preferences to create varied design prototypes for different user segments. 🛠️ Engineering Handoff: AI engineers, understanding design intent and user needs, optimize code efficiently, ensuring seamless transition. 🔍 Quality Assurance: AI algorithms in QA dynamically test products, adjusting parameters based on real-time data for comprehensive coverage. 📈 Product Management: An AI product manager aligns product strategies with market trends, competitor analysis, and user feedback. 📣 Marketing and Sales: AI-driven marketing and sales analyze data, predict market response, and dynamically adjust strategies based on feedback. Feedback Loop and Iteration: Market performance feedback flows back to the AI designer, informing improvements with rich, contextual insights. With each cycle, AI systems refine, learning from past outcomes to enhance product design and market strategies. 🔁 This AI-driven feedback loop shatters traditional, linear workflows, creating a hyper-adaptive system that redefines product creation. It blurs the boundaries between development, analysis, and consumer feedback, crafting products that resonate deeply with market demands at unprecedented speed. In the AI Workspace, humans evolve from workers to orchestrators, sculpting AI workflows and directing the narrative. We set the stage for AI's performance, dictating the ordering and steps of its workflow, shaping outcomes with strategic foresight. As curators of this intelligent ecosystem, our role pivots to innovation and high-level strategy, while AI executes with a precision and adaptability we can't match. Interestingly, this shift might be the death of entry-level and middle management roles. We might be headed towards black and white employment. You’re either dictating AI workflows, or cashing in unemployment cheques. AI Workspaces herald the dawn of a new corporate species: ultra-agile, antifragile, and perpetually evolving entities. They represent a future where technology is not just a tool but an entire species governed by the same principles of natural selection. 🧬 What do you think? #AIWorkspaces #FeedbackLoopI #FutureOfWork #BusinessAutomation #AIinBusiness #Innovation #techevolution #StrategicAI #AdaptiveTechnology #career #productdevelopment