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10940_AI_Business_School_Mitra_Azizirad_FINAL

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[AI Business School] >> Mitra: Across industries, new disruptive business models, processes and entire companies are springing up with AI at their core. Early strategic adopters of AI are leveraging it for business and competitive advantage. Disruption is inevitable from a technology perspective, but it's also inevitable at the cultural level of an organization. Developing a strategy for AI extends beyond the business issues all the way to the leadership behaviors and capabilities required to instill an AI-ready culture in your organization. When driving holistic AI transformation, there are key aspects that come into play at an organization level that can prevent the successful implementation of AI. First, AI depends on both the integrity of the data as well as access to the data. Breaking through data silos, which can be fragmented across the company, as well as breaking through functional silos, requires intensive levels of collaboration and trust. Successful implementers of AI will instill a data-driven approach that breaks down these silos. Second, fostering an environment where cross-functional teamwork is encouraged and celebrated is vital. Empowering people from all functions across your company to contribute ideas, ask questions and make suggestions is important in driving change and adopting new ways of doing business. Successful implementers of AI will empower employees and foster an inclusive approach and create forums where different roles can come together to try new ways of working. Third, AI will bring new insights to you that are critical in supporting strategic decision making, perhaps recommending new actions you should take to improve performance. Ethical accountability in making these decisions needs to be scaled across the organization, because the question is not what AI can do, it's what AI should do. Successful implementers of AI will roll out a well-defined leadership and governance approach to ensure the right actions are being taken in a transparent and explainable way. To have a data-driven culture, you need to be able to reason over your entire data estate, whether it's on prem, in the Cloud or on the edge. The ability to access the full breadth of data in real time across your organization promotes decision making at unprecedented scale and speed, And this is what truly transforms your business. Breaking data silos, regardless of data ownership, or where the data lives, is vital. Fostering a culture where data is openly shared and getting groups to work together to train models is essential. This can take the form of creating agreements with other departments to ensure everyone is getting access to the data they need. This makes AI models more relevant, accurate, and therefore exponentially more useful. But it's not only about accessing the entire data estate. it's also about ensuring that the data is high quality. Ensuring you have the best and most complete data as the foundation for your AI systems is of paramount importance. This became clear to us when we first rolled out a new approach at Microsoft using AI to score marketing leads. At the outset, we saw that the models were returning highly-improbable results. As we looked at our CRM, it was clear there was a disconnect between our technologists and our sales people in terms of how the data was being used. Leads were being erroneously disqualified. We quickly learned that we need to foster a collaborative forum, one where we brought our technologists together with our sales people to share how AI models were being used, underscoring the need for highly-accurate data. We also had the sellers share with the technologists what types of data were most useful to them in scoring the leads. Based on those learnings, we made cultural changes in our approach, and the results coming from the AI models improved dramatically. Next, fostering an inclusive environment, where all employees, whether technical or not, are empowered to participate in the AI transformation is critical. Creating an AI-ready culture is predicated on the willingness and ability of employees to work in cross-functional teams that cut across organizational boundaries, encouraging them to collaborate in new ways and with people they may have never had to work with before. An AI-ready culture is one where the creating and sharing of ideas, new and different ways of working, and continuous learning and experimentation is encouraged and rewarded. It's important that this extends beyond technical employees. Many of the best ideas in the strategic implementation of AI come from empowering employees closest to the business who are better able to see the new business opportunities, as opposed to data scientists or analysts. For example, our compliance-predicting analytics tools were inspired and developed by employees working on our finance teams because they were the closest to the business need. Empowering and rewarding employees across your organization, regardless of role, to come forward with new ideas is a key ingredient for success. Finally, change is everlasting. As data changes and AI models evolve, business outcomes can shift. In the age of AI, leadership needs to be nimble and responsive to managing change. Cultural change is driven largely by leaders, and requires an approach that generates energy and inspires employees. It also requires a governance model that fosters and rewards this kind of culture, transformational challenges and addresses the AI brings, both operational and ethical. On the Microsoft front lines, engaged and inspirational leaders were critical to motivating our employees and ensuring rapid adoption of new AI processes that we rolled out to our global sales force. As organizations look to a future full of opportunity powered by AI, it's important for leaders to take on responsibility and accountability in addressing the ethical challenges AI poses. Creating a set of principles and operationalizing governance processes to support them is very important because in an AI-ready organization, trust is vital. And trust requires transparency and clear, ethical guidelines that are scaled across the organization, becoming core to you and your employees' decision making. At Microsoft AI governance started with our CEO, Satya Nadella, establishing six key principles that guide our employees in building, using and applying AI. But this approach would not have been successful without our managers embracing and leading the change through systems and behaviors from a documented ethical design guide to how we review our employees and distribute rewards and compensation. Implementing AI across your organization requires organizational flexibility, a data-driven environment, new forms of collaboration with cross-functional teams, all supported by strong, inspirational leadership and clear, ethical standards and governance. Our executive team at Microsoft is pleased to share insights, learnings and key challenges we faced at Microsoft, as we focused on creating an AI-ready culture.

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Posted by: csintl on Jun 19, 2019

10940_AI_Business_School_Mitra_Azizirad_FINAL

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