- AI & Machine Learning
- Internet of Things
- Edge Computing
Emerging & Disruptive Technologies
Technology is changing everything, and the rate that technology is changing is accelerating and will never be this slow again. CIOs must identify and capitalize on trends that are driving significant change. IT leaders must understand that data is the epicenter of digital transformation and that making data actionable is the new calling of IT professionals.
Yet, another developing trend complicates this. Business leaders are increasingly driving IT decisions, requiring a new type of IT leadership to align with these business decisions. Moreover, businesses are increasingly interconnected through people and things. The rapid expansion of these digital ecosystems makes the management, protection and proliferation of an organization’s data a daunting task. Staying the traditional course will at best make you a laggard, but will more likely end your business and your career.
1. How has Emerging & Disruptive Technologies topic evolved since last year? Have you noticed any major changes in the market, strategy or technology?
A: This year, there is a big thrust on megatrends, with many leaders seeking to respond to the risks and opportunities around disruption. Many enterprises are realizing that the leadership, roles and organizational structures that they have are insufficient to disrupt the status quo. This is a key impetus for the new roles we are seeing in enterprises such as Innovation officers and others such as CDOs that have been there for a while.
2. What’s one of the biggest mistakes organizations make when it comes to this topic?
A: They adopt new technologies but do not make sufficient changes in their risk management and operating models. Also, technology adoption alone isn’t sufficient and needs to supplement by culture hacking and empowering the right people. Furthermore, innovation to be truly transformational needs to involve changes across processes, systems, business architecture, strategy and governance.
3. How are IT leaders leveraging this topic to transform their organizations?
A: Organizations with visionary leaders and strong culture are embarking on “creative destruction”, challenging status quo and rearchitecting their platforms (while most others are fine with an incremental change. Strong leadership and an open, innovative culture is often what determines success or failure. Emerging and disruptive technologies are leveraged by IT leaders to drive new business and operating models and drive growth in their organization.
4. Finish this sentence: “If organizations don’t get their digital business transformation right, they will….”
A: Many of them will perish and the others will go through an endless cycle of trying to figure out the right business and operating model and recruit a strong leader to remain relevant. Digital disruptions creates risks and opportunities, which need to be grasped by companies.
5. How attending Gartner IT Symposium/Xpo 2020 will help IT leaders with their priorities and key initiatives?
A: We deliver pragmatic advice to IT leaders on how to be successful with a digital transformation through a holistic prism that covers technology, people, process and culture. Moreover, Gartner events are a great avenue to understand real case studies, innovation playbooks and how successful companies do it.
Over the last few years, the pace of innovation in AI technologies has been staggering, predominantly coming from small vendors. CIOs are in the perfect position to educate the company’s CEO and board about recent developments in AI and illustrate how AI might influence their business and their competitive landscape.
By following this approach, CIOs can potentially flip the traditional engagement model between IT and the business, influencing business strategy at the outset, rather than simply developing implementation projects that follow up on the executive team’s decisions.
AI will be used to render new insights, transform decision making and drive improved business outcomes. It includes many areas of study and technologies behind capabilities like voice recognition, NLP, image processing and others that benefit from advances in algorithms, abundant computation power and advanced analytical methods like machine learning and deep learning. These rapidly advancing capabilities are behind new business models based on data and a wide-range of impacts across the enterprise. Most organizations may not pursue the leading-edge uses of AI, such as building robots and self-driving cars; however, AI will play an increasingly important role in the top-three business objectives cited for the office of the chief data officer (CDO) - greater customer intimacy, increasing competitive advantage and improving efficiency.
While many enterprises will be content to leverage applications incorporating new capabilities, enterprise leaders should understand leading use cases, determine where the greatest potential exists for AI technologies, assess where “quick wins” can be obtained and determine organizational responsibilities to address the breadth of opportunities. At its core, AI is about solving business problems in novel ways. It stretches across any organization from innovation, R&D and IT to data science.
IoT is not a technology looking for a business problem. Perhaps more than any technology initiative of our age, IoT will be business-driven.
Businesses are driven by two immutable forces: making money (that is, generating revenue) and saving money (that is, operational efficiency). IoT serves both of those masters. By connecting and instrumenting things, business can be more responsive to clients, react faster to issues and create new business opportunities, all of which can help make and save money. Hence, most IoT solutions will start as business-led initiatives to create new business value.
IoT will spur a new wave of IT systems to store and analyze the flood of data generated by thousands or millions of devices, or “things.” The unprecedented volume, velocity and variety of this data will force organizations to change their IT infrastructures — especially their data management and analytics infrastructures — and to adopt new platforms, practices and mindsets.