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AI Revolution: Practical Takeaways for Decision Makers

We are pleased to share the article by Moti Krispil, a partner with Strauss Strategy, in shaping and implementing an “Organizational Operating System” for CEOs and decision-makers, aimed at smart business and organizational navigation of AI transformation.

The Elephant That Learned to Dance: Morgan Stanley’s AI Revolution and Practical Takeaways for Decision Makers

Shall we start with some small riddles? 🤔
How do you get 98% of 15,000 advisors to use a personal AI assistant within 9 months❓
How do you reduce client report preparation time by 70% without compromising quality❓
How do you increase customer satisfaction by 28%❓
And how do you boost advisor efficiency by 35%❓

The answer? Morgan Stanley. 🎭

Introduction: The Bold Move of the Wall Street Giant

Morgan Stanley, the financial giant with an 88-year history, is not just one of the five largest brokerage firms in the world. With 80,000 employees in 42 countries, it manages assets worth $5.5 trillion (!). Among its clients are no less than 60% of the Fortune 500 companies, and now it is leading an AI revolution that could reshape the world of finance as we know it. 🌍💼

In the financial world, where caution is often the name of the game, Morgan Stanley surprises with its bold approach to adopting artificial intelligence (AI). This is a story of innovation, managerial courage, and digital transformation on a remarkable scale.

💡 Major Initiatives: AI at Work

Before we dive deep into the strategy, here’s an overview of the key initiatives Morgan Stanley has implemented:

🤖 Development of innovative tools to empower employees.

🤖 🤖 AI @ Morgan Stanley Assistant

What is it? A smart AI assistant for financial advisors.
What does it do? Provides quick access to research, analyzes market trends in real time, and offers personalized investment recommendations.
Results: 98% of advisors adopted it, with a 35% increase in efficiency.
Anecdote: In the first week of launching the system, one advisor identified a rare investment opportunity that generated millions in profits for the client. “It’s like having Warren Buffett as a personal assistant,” the advisor exclaimed.

🤖 🤖 AI @ Morgan Stanley Debrief

What is it? An AI system for managing client meetings.
What does it do? Summarizes video meetings, drafts follow-up emails, and integrates with tools like Outlook and Salesforce.
Results: Saves an average of 42 minutes per client meeting and increases customer satisfaction by 28%.
Interesting insight: The system not only saves time but also identifies patterns in customer behavior that human advisors might miss. For example, it noticed that clients tend to be more open to new ideas at the beginning of meetings.

📚 Comprehensive Training and AI Culture Integration

Basic AI training for all 60,000 company employees.
Appointment of 500 “AI Ambassadors” from various departments to lead the change.
Creation of a personal “AI score” for each employee, influencing performance evaluations and rewards.
Challenge: Initially, employees feared that AI would replace them. Morgan Stanley addressed this by emphasizing the empowering role of AI and creating personalized training programs.

🤝 Strategic Partnership with OpenAI

– 50 engineers from OpenAI are working full-time on Morgan Stanley projects.
– Access to advanced models 6 months ahead of competitors.
Insight: The partnership wasn’t just technological. It created a “mutual exchange” of ideas between the world of finance and AI, leading to the development of innovative applications that neither side would have achieved on their own.

📊 Continuous Assessment and Improvement

– Creation of dedicated AI performance metrics.
– Quarterly review of progress and adjustment of the strategy accordingly.
Anecdote: During one of the quarterly reviews, it was discovered that a particular department was struggling to adopt AI. Instead of placing blame, Morgan Stanley organized an “AI Hackathon” for the department, which led to the development of a custom AI tool that became a hit across the entire company.

🧠 Strategic Insights: What Every Manager Can Learn from Morgan Stanley

🍳 Organizational Culture Eats Technology for Breakfast

At Morgan Stanley, they understood: you can’t “force AI.” That’s why they created an organizational culture that celebrates innovation, encourages learning, and invests in training all employees, from the janitor to the CEO.

Tip for managers: Create a “buzz” around AI in the organization! Share articles, organize “Lunch & Learn” sessions, and make the conversation accessible and relevant to everyone. Even without a huge budget, you can start small – share relevant articles, encourage self-learning, and celebrate “small wins” in AI implementation within teams.

💰 A Smart Mix of ‘Take, Shape, Make’

Morgan Stanley wasn’t afraid to combine internal development, off-the-shelf solutions, and strategic partnerships with leading companies like OpenAI. The result? Flexibility and a quick response to market changes.

The right balance: Morgan Stanley chose to develop about 60% of solutions internally, purchase 20%, and partner on the remaining 20%. This allowed them to maintain a competitive advantage in core areas while efficiently leveraging external resources.

Tip for managers: Map out your AI needs. Maybe an existing solution meets them, or perhaps a small startup can offer unique capabilities you lack. Be creative and seek partnerships that can propel you forward!

📊 AI that doesn’t serve the customer is just useless data

At Morgan Stanley, every AI project is evaluated through one lens: “distinct customer value.” They implemented a “digital shadow” for each customer, personalizing at the individual level and ensuring full transparency – all to create an exceptional customer experience.

Anecdote: One of Morgan Stanley’s major clients was skeptical about using AI. The company invited him to a “day in the life of AI,” where he saw how the systems worked in his favor. By the end of the day, not only was he convinced, but he also requested to invest in AI companies.

Tip for managers: Ask yourself – how can AI improve your customers’ experience? Focus on the weak points and look for AI solutions that can make a real difference.

🏆 “Small Wins” on the Path to Big Success

Morgan Stanley understood: you can’t “swallow” AI all at once. Alongside their massive investments, they implemented a “quick wins” strategy – small projects that delivered fast results and built trust in AI within the organization.

Example: One of the “quick wins” was the development of a simple AI bot that answered common HR-related employee questions. This saved a significant amount of time for the HR department and demonstrated to employees the effectiveness of AI in everyday tasks.

Tip for managers: Identify 2-3 processes that can be immediately improved with AI. Start small, celebrate successes, and show employees that AI is no longer science fiction, but an effective tool already working for you.

🔮 Looking Ahead: Challenges and Next Steps

Challenges Ahead

Regulation: Dealing with evolving AI regulations in the financial sector.
Data Security: Protecting sensitive customer data in the AI era.
Human-Machine Balance: Maintaining the human touch alongside advanced automation.

Response: Morgan Stanley established a dedicated “AI Ethics and Regulation” team that works closely with regulators and ethics experts.

Next Steps

AI for Risk Management: Development of a dedicated AI model for risk management, expected to save $1.5 billion annually.
Ethics and Responsibility: Establishment of an AI Ethics Council in collaboration with academia.
Empowering the Human Advisor: Expansion of the “AI Augmented Advisor” program to further empower human advisors.

🎯 Summary: Key Takeaways for Every Organization

Morgan Stanley’s journey demonstrates that adopting AI goes far beyond technology. It’s a fundamental shift in how an organization thinks, operates, and delivers value.

A flexible strategy: Morgan Stanley developed an adaptable AI strategy that could quickly adjust to changes in technology and the market.
A roadmap with flexible joints: The company created a long-term plan, but with frequent checkpoints and updates, allowing real-time adjustments.
Balancing customer and employee focus: Morgan Stanley understood that AI’s success depends on improving both customer experience and employee empowerment.
Culture before technology: Invest in building an organizational culture that embraces and encourages innovation. Morgan Stanley created an “innovation ecosystem” where every employee felt part of the revolution.
Hybrid approach: Combine internal development, off-the-shelf solutions, and strategic partnerships. This flexibility allowed Morgan Stanley to respond quickly to market changes.
Customer-centric focus: Every AI project should ultimately enhance the customer experience. Morgan Stanley made this an organizational mantra.
Quick wins: Start small, show quick results, and build momentum. This was key to creating positive “buzz” around AI in the organization.
Long-term thinking: Define a long-term AI vision and work consistently to achieve it. Morgan Stanley didn’t see AI as a one-time project but as a long-term strategic shift.

Morgan Stanley’s revolution shows that the future of AI in finance is already here. The question isn’t whether to join the revolution, but how to lead it – at any scale.

“AI is not a tool, it’s a way of thinking. We’re not just implementing technology, we’re reshaping how we work, think, and make decisions.” – Andy Sage, Senior CTO at Morgan Stanley.

Final Thought: Morgan Stanley’s journey shows that successful AI integration isn’t just about the technology itself but the ability to incorporate it holistically into every aspect of the organization. It requires vision, leadership, and yes – a bit of courage. But as Morgan Stanley has proven, the results can be extraordinary.

So, are you ready to start your journey toward an AI-powered future?

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Charging for the Future: The Story Behind the Business-Digital-Technological Journey of Leading Electric Vehicle Charging Provider EV-Edge

The story of EV-Edge begins with a vision – a vision to become the market leader in electric vehicle charging in Israel. With more than 2,300 managed charging outlets and over 5,000 unmanaged outlets spread across the country, and a user base of over 40,000 registered users representing Israel’s electric future, EV-Edge is now the dominant player in this market. But like any forward-looking company, EV-Edge understood that there are moments when a significant leap is necessary – to upgrade business-digital capabilities, enhance the customer experience, and improve tools and technology to continue leading into tomorrow.

The Challenge of a Fast-Growing Market

The electric vehicle market in Israel is growing at a rapid pace, and drivers’ expectations are rising with it. EV-Edge, part of the Union Group (which represents brands such as Toyota, Geely, Lexus, and Zeekr in Israel), realized that in order to maintain its position as a market leader, it must upgrade its core system in the world of charging management (EV CMS). The existing system has served EV-Edge well over the past five years, but like any business-technological system, it has reached a stage where it can no longer meet the evolving and complex demands of the market.

This challenge is a key part of a deep strategic business-digital-technological process that began about two years ago, led by Strauss together with EV-Edge’s management. This rapid and highly practical initiative involved defining EV-Edge’s strategic goals and objectives within the company’s business-digital-technological roadmap, including the recommendation to replace the CMS system. At this stage, the objectives and projects for implementation in various areas were defined. In this realm of charging management, a clear task was set: to help EV-Edge find, define, and implement a new system that is robust, flexible, and powerful – one that can handle any challenge and provide an excellent user and customer experience in every aspect.

The Quest for the Perfect System

The search for a new system is not just a technical process but a fascinating business, organizational, and technological quest where every small detail can make a difference. This process involved evaluating six different alternatives, each with its own advantages and disadvantages. Some of the alternatives were developed by companies focused on projects, while others belonged to companies with a product-oriented approach. These two approaches produce entirely different solutions and raise critical questions: What kind of support will be provided? Will the solution adapt to the evolving needs of the market? What will be the impact of this decision on existing customers? And more.

To ensure nothing was left to chance, EV-Edge decided to take a hands-on approach and install real charging stations at various sites for comprehensive field testing. The CEO, an outstanding engineer and Technion graduate, insisted on a professional and meticulous process down to the last detail. The companies being evaluated were highly impressed by the depth and professionalism of the process, experiencing a level of examination unlike any other.

Upgrading with no Interruptions

The final decision was made, but the journey didn’t end there. The migration process that began was vast in scale and complexity – integrating hardware, software, and new charging stations with relevant business processes, along with the transition of over 100,000 existing customers, including their personal details and payment models. All of this was done without causing customers to feel any changes or lose even a minute of charging time. It was a complex and unprecedented process, but one that solidified EV-Edge’s position as the market leader, with a modern, reliable, and advanced system.

The new system also included a variety of APIs that allow third-party companies and entrepreneurs to create and provide added value to customers through it, with personalized (data-driven) experiences, expanding possibilities and enhancing the customer experience to levels never before seen in Israel.

The Experts Led the Way

Throughout the entire process, Strauss Strategy’s team of experts in the business, digital, data, technology, and infrastructure sectors, as well as in change management, supported EV-Edge’s managers. From the very first stage of defining the business-digital-technological roadmap and building a detailed work plan for its execution, through the rapid transition to formulating the requirements for the core system and the business processes it supports, to leading the evaluation process of alternative systems and selecting the new system, and finally to its successful implementation and launch. The result is the most advanced electric vehicle charging management system in Israel, ensuring that EV-Edge will continue to lead this growing market in the years to come.

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The Rise of AI Agents

AI agents are changing the way we interact with AI engines as well as with the world around us. Smart AI-based applications are designed to communicate with the defined business environment, collect data, and perform tasks independently to achieve pre-set goals.

The concept of autonomous AI agents – LLM-driven bots capable of thinking and completing tasks independently – gained tremendous momentum in 2023. Now, the field is flourishing. Research firm CB Insights reports that more than 50 startups have been developing and delivering smart AI agents since 2022, a number expected to rise, possibly even doubling in the coming year.

The Marker recently addressed this trend: “Chatbots like ChatGPT are already a thing of the past. The future lies in AI agents. While chatbots pull answers out of a hat, AI agents are trained to work carefully and methodically to deliver more accurate results.”

Enterprise organizations in Israel are developing smart agents for their own use or to sell to clients, and more and more startups focused on AI agents are emerging. Globally, there are already startups raising significant funds, such as Cognition AI from San Francisco, which is developing an AI agent for programmers. The company was founded only in November 2023 and has already raised $200 million, with a valuation of $2 billion in the latest round.

Although humans define the business goals and objectives, the AI agent is the one that independently chooses the best actions to meet the defined needs. This autonomy makes AI agents highly flexible and particularly useful across a wide range of applications—from customer service to content creation, and beyond. It is no surprise that they are expected to disrupt business operations across various industries. Below are a few examples and explanations of AI agents and how they might impact the business reality for all of us:

Let’s start with the basics: What are AI Agents?

AI agents are software applications powered by artificial intelligence, designed to perform specific tasks independently or with minimal human intervention. Unlike traditional AI systems, which primarily focus on data analysis or providing recommendations, AI agents are action-oriented. They can execute a series of tasks, often integrating multiple systems, to achieve a desired outcome (always defined by a human).

The main characteristics of AI agents:

  • Independence: AI agents operate independently once given a task, often making decisions and taking actions without human involvement.
  • Task-oriented: These agents are built to complete specific tasks, ranging from customer interactions and solving complex technical issues to HR functions, like onboarding new employees.
  • System integration: AI agents often bridge different software systems, pulling data from one system, processing it, and then acting within another system, seamlessly integrating different aspects of the workflow.
  • Learning and adaptation: Over time, AI agents can learn from their interactions and experiences, improving their efficiency and effectiveness in completing tasks.
  • Scalability: AI agents can handle large volumes of tasks simultaneously, mking them highly scalable solutions for businesses looking to automate repetitive or complex processes.

 

Examples of AI agent use cases:

  • Customer service: AI agents can engage in conversations with customers, process their requests, and offer product or service recommendations, reducing the need for human intervention.
  • Human resources: AI agents can automate processes like resume screening, scheduling interviews, and onboarding new employees.
  • Technical support (IT): AI agents can diagnose and solve technical issues, install updates, and even manage security protocols. For example, according to The Marker, the startup Atera, which develops a system for IT support teams in organizations, has created a virtual representative that automatically resolves some service requests, such as users needing password resets. Atera started working on such a system as early as 2017, but without satisfactory results. The breakthrough came only with the new language models. Today, Atera markets an agent installed on users’ computers that provides automatic solutions to problems like programs not opening or a slow computer. Atera’s agent can run diagnostics to identify the cause of the slowdown and then make the necessary changes to the computing systems. 

 

So far, we’ve covered the main characteristics and a few practical and business use cases for the near future. But let’s also talk about the future potential:

As AI-based technologies advance and evolve, AI agents are expected to take on increasingly complex tasks and might even manage entire business processes or make strategic decisions entirely autonomously. They could evolve to handle tasks that require more contextual sensitivity, such as personalized marketing campaigns, complex research, or even medical diagnoses.

Challenges and Considerations:

  • Ethical considerations: As AI agents become more independent, ethical concerns regarding decision-making, privacy, and accountability will arise.
  • Integration: The integration of AI agents with existing systems and workflows could create business, operational, and legal challenges, and may require significant technical adjustments by the organizations.
  • Human oversight: It’s important to ensure that AI agnets operate within desired parameters and align with the company’s values and goals. Most organizations today incorporate a layer of human management and monitoring to ensure that AI activities meet the business standards representing the organization.

 

In conclusion, while excitement around AI agents is high at the moment, the tools in this field are still in their early stages, and their commercial potential has yet to be proven. This potential depends on their ability to deliver reliable, high-quality, and secure results that people and organizations can trust.

Every company focusing on this area is seeking its own solutions to achieve such results. For example, at Atera, they limit their AI agent to tasks where it cannot cause harm to the organization’s systems. Enso, on the other hand, tailors each AI agent they develop to a specific industry. An agent designed to write blog posts for lawyers, for instance, is directed only to legal databases—and not the entire internet—to reduce the chance of including unrelated information.

At Strauss, we will continue to follow this hot trend and share updates on new developments through our channels.

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How to create a bi-monthly work plan using Agile methodology?

The phrase “time is valuable” takes on a whole new meaning when discussing work plans and the time they typically require in most organizations. But Menora is not just any organization. In 2023, Yaki Zino, head of the IT department, defined a new vision for the division: to adopt a methodology focused on short-term planning (a new plan each quarter). After deliberation and management approval, it was decided to shorten the timelines further and create a new plan every two months!

This decision builds on a previous process we carried out with the department: the adoption of the Agile methodology, working in sprints, and planning and executing tasks in the short term (rather than on an annual basis).

The Challenges:

In a large financial institution like Menora Insurance, there are multiple business units, which naturally diversifies the goals and objectives, making it challenging to create a new task plan every two months. To tackle this, key strategic focuses were defined, to which the entire division is aligned and committed. The business side consolidates and submits its requirements (aligned with one or more of the strategic focuses), and the IT department analyzes and refines them. This process results in a focused, short-term work plan.

At the beginning of 2024, the department adopted a completely new perspective on the concept of “work plans”:

  1. The foundation of the new approach: planning no more than two months ahead – this includes everyone, with all the implications that entails.
  2. Centralized task management: All involved parties consolidate and manage task information in one place (the Jira system), ensuring order and effective management while also providing broad holistic transparency.
  3. Closing gaps and approving the plan: To finalize the upcoming plan, every two months, a day is set aside where senior department leaders, heads of divisions, and department heads gather from morning until late afternoon. During this time, they resolve conflicts, address challenges, and consider all relevant constraints, with the goal of concluding the day with a closed and approved plan.
  4. Communication and transparency: Adopting and successfully implementing the new methodology in practice takes time. However, as the department progressed alongside its business partners, they learned the importance of mutual commitment to the success of the process. The business teams understood that for the IT department to meet tight deadlines and deliver the required outcomes on time and with high quality, they must provide clear, detailed requirement documents, commit to being available to clarify needs during development, and approve small deliverables as they are completed.
  5. What happens when changes and adjustments are needed? Changes and adjustments are part of business reality, and flexibility is a critical feature in a competitive market. To address this, a procedure was established to assess the impact of changes on the continued implementation of the entire plan. If the change does not affect the committed work plan, they proceed. If there’s a risk of disruption, it’s escalated to management, but there’s always support. The real value comes from the level of commitment and dedication of all involved to the process.
  6. Ongoing monitoring: Continuous close monitoring of the pace and progress in Jira provides a safety net, aiming to identify risks in real time that could delay the plan.

 

In conclusion: This change is possible. Nir Yaakov, the expert who led the project at Menora on behalf of Strauss Strategy, said: “Even traditional organizations that have been accustomed to working with certain methods for years can successfully adopt and implement new and different methodologies, ones that generate significantly higher productivity than the existing processes. However, it’s important to recognize the critical role of senior management commitment. Without strong leadership support, such a change cannot be fully realized.”

Want to learn more about adopting Agile processes? Interested in understanding how to create short-term work plans?

Our team of experts is here for you and would be happy to share from our extensive experience working with leading organizations in the industry.

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