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The past decade in IT has been all about digitaltransformation. Transformations once envisioned to be a two- or three-year journey, to catch up or get ahead, have become a continuous journey with no end in sight. The philosophy behind adaptive systems is more about innovation than riskmanagement.
Last week, I had the distinct privilege to join my Gartner colleagues from our RiskManagement Leadership Council in presenting the Q4 2018 Emerging Risk Report. We hosted more than 500 risk leaders across the globe in our exploration of the most critical risks.
As organizations shape the contours of a secure edge-to-cloud strategy, it’s important to align with partners that prioritize both cybersecurity and riskmanagement, with clear boundaries of shared responsibility. An organization’s approach to security must also scale at the speed of digitaltransformation.
Modern EA strategies now extend this philosophy to the entire business, not just IT, to ensure the business is aligned with digitaltransformation strategies and technological growth. The process is driven by a “comprehensive picture of an entire enterprise from the perspectives of owner, designer, and builder,” according to the EABOK.
Rather than simply investing in technology, and hoping for the best, however, IT leaders need to be strategic and undertake riskmanagement that best suits their business profile. Fortinet research shows that 64 per cent of A/NZ organisations agree that the skills shortage creates additional risks for their businesses.
As organizations shape the contours of a secure edge-to-cloud strategy, it’s important to align with partners that prioritize both cybersecurity and riskmanagement, with clear boundaries of shared responsibility. An organization’s approach to security must also scale at the speed of digitaltransformation.
As data continues to grow at an exponential rate, our customers are increasingly looking to advance and scale operations through digitaltransformation and the cloud. For logistics and supply chain, this may include managing predictive maintenance, connected vehicles and fleet management.
With more and more companies undertaking the journey of digitaltransformation, the role of the CIO has become critical. He brings expertise in developing IT strategy, digitaltransformation, AI engineering, process optimization and operations. He will also plan and implement the company’s IT and digital strategy.
AI and data science dominate the agenda As companies proceed with digitaltransformation efforts , their focus is firmly on enabling business outcomes with data, increasing demand for data science, analytics, AI, and even RPA skills. These include not only cyber, but also cloud and generative AI, he says.
In his current role as chief information and digital officer at WestRock, he’s responsible for developing and executing global information systems, technology, and cybersecurity strategy in addition to leading the company’s digitaltransformation. How do we strengthen our operations?
and other technologies for digitaltransformation of manufacturing systems. By linking this data, they facilitate tasks like asset management, predictive maintenance, documentation management, mission planning, riskmanagement, aircraft design and optimization, and anomaly detection.
EAM systems can include functions like maintenance management, asset lifecycle management , inventory management and work order management, among others. Predictive and preventive maintenance : The advent of IoT and AI technologies has transformed EAM systems into predictive maintenance tools.
Not just banking and financial services, but many organizations use big data and AI to forecast revenue, exchange rates, cryptocurrencies and certain macroeconomic variables for hedging purposes and riskmanagement. Integrating IoT and route optimization are two other important places that use AI. AI in Healthcare.
For Namrita, Chief Digital Officer of Aditya Birla Chemicals, Filaments and Insulators, the challenge is integrating legacy wares with digital tools like IoT, AI, and cloud platforms. For instance, AI-driven predictive maintenance and digital twins can reduce maintenance costs by 20%, optimizing production and supply chains.
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