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! ••••••••••••••••••••••••••••••••••••••••••••••
Strategies for AI-Driven Growth in Technology Companies
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Summary
Strategies for AI-driven growth in technology companies focus on integrating artificial intelligence to streamline operations, enhance decision-making, and upgrade roles to achieve sustainable progress in a competitive landscape.
- Prioritize clear goals: Start with identifying specific business problems AI can solve, and align projects with measurable outcomes to ensure meaningful progress.
- Empower your workforce: Train employees to adapt to AI-driven workflows, shifting their focus toward creative, strategic, and human-centered tasks.
- Adapt your structure: Move towards agile, cross-functional teams and reassess roles regularly to integrate AI tools and encourage innovation.
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Most companies fail at transforming their GenAI pilots into sustainable business value. This excellent overview from Stephan Bloehdorn and his team highlights some best practices for scaling AI solutions at enterprises: 1. 𝐒𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐝 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡: - Adopt a product & platform engineering model, focusing on cross-functional teams. - Design AI-powered digital workflows with a focus on clear business outcomes rather than just tech. 2. 𝐅𝐥𝐞𝐱𝐢𝐛𝐥𝐞 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞: - Implement a modular Data & AI platform to adapt to future AI advancements, manage costs, and streamline integration. 3. 𝐒𝐨𝐥𝐢𝐝 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬: - Embrace standardized processes across all Data & AI implementations, to guarantee quality, repeatability, and efficiency. - Common tactics include building templates and automations for data and model workflows. 4. 𝐄𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞-𝐰𝐢𝐝𝐞 𝐋𝐢𝐭𝐞𝐫𝐚𝐜𝐲: - Invest in upskilling all employees in Data & AI - Foster a culture ready to identify valuable use cases and leverage new AI tools 5. 𝐑𝐨𝐛𝐮𝐬𝐭 𝐀𝐈 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞: - Develop comprehensive AI governance frameworks to ensure compliance, risk management, and model lifecycle oversight. - Support this with the right tools and checks 🤔 𝐖𝐡𝐚𝐭 𝐚𝐫𝐞 𝐬𝐨𝐦𝐞 𝐨𝐭𝐡𝐞𝐫 𝐛𝐞𝐬𝐭 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬 𝐲𝐨𝐮'𝐯𝐞 𝐬𝐞𝐞𝐧? 🔎 Detailed case studies and additional info in comments. -------- 🔔 If you like this, please repost it and share it with anyone who should know this ♻️ and follow me Heena Purohit, for more AI insights and trends. #artificialintelligence #enterpriseai #aiforbusiness #aiapplications #aiadoption
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💬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
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AI implementation meetings: 5 People. 0 Strategy. Here is where most companies fail. 👉 They jump straight into tools. Vendors. Demos. Dashboards. And call it a strategy. But AI only delivers results when the basics are in place. 📌 A clear business problem 📌 Clean, usable data 📌 Humans who are ready to act Without that? You’re not running a transformation — You’re hosting an expensive guessing game. 7 Moves to Make Your AI Strategy Actually Work: 1. ✅ Define the problem. - AI should solve a specific business need. - If it doesn’t, it’s just a shiny distraction. 2. ✅ Audit your data. - Garbage in, garbage out. - You can’t fake good data. 3. ✅ Pick use cases, not buzzwords. - “GenAI” isn’t a strategy. - “Reduce customer churn by 12%”? That’s a use case. 4. ✅ Loop in your integration team early. - AI isn’t plug-and-play. - Especially not with your 14 legacy systems. 5. ✅ Prep your people. - The biggest blocker isn’t the model. It’s mindset. - Train your team for the change. 6. ✅ Set KPIs before kickoff. - What does success look like? - How will you measure progress? 7. ✅ Assign ownership. - If everyone’s responsible, no one is. - Give someone the wheel. 🧩 Botom Line: If your AI “strategy” fits on a single flip chart… You’re not building transformation — You’re throwing corporate darts at the future. ♻️ Repost if you’re investing in people, not just tech. 👣 Follow Janet Perez for more like this.