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.

Artificial intelligence

Over the past few years, the pace of innovation in artificial intelligence (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.

The Internet of Things

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.

Hot topics that were covered at Gartner IT Symposium/Xpo® in 2019:

  • AI and machine learning
  • Blockchain
  • RPA
  • The Internet of Things
  • Edge computing

Expert Q&A with David Furlonger, Distinguished VP Analyst

Artificial intelligence (AI) specifically and other elements of data and analytics are creating a new form of work — the augmented skill set. People-based intelligence is being enhanced and extended with new automation skills to save time and money and new innovating capabilities to drive new solutions to current and new challenges. AI is helping to develop augmented data and analytics.

More specifically, hybrid approaches in natural language processing (NLP) are using semantics to improve NLP accuracy and effectiveness. This may help with outcomes ranging from cost savings, through to business growth, innovation, and improved or newly enhanced customer experience and engagement practices, and processes. However, this is not automatically assured by spending money simply on AI.

At a technology level, more organizations are moving away from a do-it-yourself effort and are leveraging more packaged AI capabilities.

Too many organizations are taking AI for granted. Too often it is assumed it will “work” as advertised by the vendor. It is assumed that AI is mature enough that if given the data it needs, it will produce results. It is also assumed that a solution to a problem that is based on AI or built around an AI-based model is needed. AI is the new silver bullet, so it surely can help with every challenge, right? Wrong. Too often, traditional technologies and techniques might be superior and ready to solve problems; however, these are often being bypassed by users who just jump on the AI-based offering. This leads to excessive costs, and worse, failed implementations and unmet challenges.

In addition, organizations tend to take a “scatter-gun” approach with AI and do proof of concepts all over the place. It would be more effective to understand the nature of the technology and its capabilities, and limitations, to target specific areas where AI can add value. Plus, the feedback analysis that helps AI learn how the predictive output can be further tuned is a critical capability often overlooked.

AI is becoming a critical enabler for digital business and digital transformation. At its root, AI can offer new ways to improve how processes and work can be automated, but equally, it can help with discovering new insights from data that users would not have ordinarily found. These two capabilities, innovation and automation, are core to digital business. Current business moments should be automated and simplified, and new innovative business moments opportunities need to be discovered and invented. One approach reduces costs and streamlines work; the other, leads to innovation and growth.

… either perish or 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 create risks and opportunities, which need to be grasped by organizations.

Attending Gartner IT Symposium/Xpo will help IT executives with their AI priorities and key initiatives by providing insights into new opportunities and how to mitigate challenges and reduce skills gaps. In addition, the conference provides best practices to help organizations move from proof of concept to more concrete and actionable AI-driven initiatives. 

Q&A with Robert Handler, Distinguished VP Analyst and Marc Kerremans, Sr Director Analyst on emerging and disruptive technologies

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 chief digital officers that have been there for a while.

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 be supplemented 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.

Organizations with visionary leaders and strong culture are embarking on “creative destruction,” challenging the status quo and rearchitecting their platforms (while most others are fine with an incremental change). Strong leadership and an open, innovative culture are often what determine success or failure. Emerging and disruptive technologies are leveraged by IT executives to drive new business and operating models and drive growth in their organization.

… either perish or 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 create risks and opportunities, which need to be grasped by organizations.

Emerging and disruptive technologies spotlight sessions from 2019:

How Oil and Gas CIOs Can Transition to Disruptive Strategies  Simon Cushing, Sr Director Analyst, Gartner

Moving Beyond the Blockchain Hype – Lessons From Early Adopters  Rajesh Kandaswamy, VP Analyst, Gartner

Making Automation Work for Your Financial Services Firm  Jason Malo, Director Analyst, Gartner