News and predictions about artificial intelligence (AI) are everywhere. Technology forecasts span the gamut, from AI ushering in world peace to machines triggering the demise of humanity.
Amidst these predictions, the terms automation and autonomy are used interchangeably. Governments and businesses alike are funding AI projects that resemble the plots of Hollywood science fiction films. And the general public has begun to fear, distrust and dread a future with AI.
What we need is less hype and more strong, practical leadership. And that leadership doesn’t necessarily require expertise in machine learning or artificial intelligence. But it does require visionary people who can create a clear strategy, motivate a diverse workforce, balance technology and business requirements, set ethical boundaries and manage the journey from where we are today to where we could be in the future.
AI leaders need to:
- Understand the strengths and weaknesses of their workforce.
- Create an environment that values data-driven analytics and empowers people to be innovative with technology.
- Value morality and ethics, and ensure that those measures encompass AI development, implementation and purpose.
Artificial Intelligence for Executives
AI requires a vision to achieve. Your vision isn’t cookie cutter, so your AI application shouldn’t be either. With our guidance, you can integrate advanced analytics, including artificial intelligence, into your strategy – and understand the strengths and weaknesses of various methods based on your goals.
AI leaders invest in people before technology
This may come as a surprise, but people are still the most valuable resource available in the realm of artificial intelligence.
When it comes to investing in AI, start by filling talent gaps in machine learning, cognitive science, analytics and infrastructure. Many companies are trying to recruit early from universities, but should invest in the existing workforce as well. They should support opportunities for education and training, and form consulting relationships with technology firms.
While some organizations are focused on the most impressive deep learning applications, leaders are looking for a variety of AI capabilities that can readily advance their business objectives across the entire enterprise. That includes investing in technical architecture, identifying pain points that can be addressed through today’s existing technology, and ensuring that all aspects of an organization are invested in and aligned to the larger strategy and growth initiatives.
Great leaders don’t have to be experts in AI, but they have to hold ownership for the outcome of all AI projects in the same way they maintain responsibility for their entire organization. Great leaders usually surround themselves with expert advisers, and AI leaders should be no different. An ideal AI advisory council would include technical experts, business stakeholders, IT directors, ethicists, marketing officers and operational leaders, to name a few.
Not every problem in the world can be solved by AI, just as not every problem in the world can be created by AI. Mary Beth Ainsworth AI and Language Analytics Specialist SAS
AI leaders drive innovation
AI is often discussed in tandem with innovation. Innovation expands far beyond algorithmic development. It includes transforming business operations, identifying new approaches to gathering and using data, discovering creative ways to apply analytical insights, and experimenting with various AI technologies to solve existing and emerging problems.
Sophistication in AI capabilities can vary based on complexities in algorithms, data, real-time deployment and compute power. Those capabilities, regardless of sophistication, can have significant impact on existing business processes, job requirements and problem-solving. AI is iterative in nature, which means operations and the human workforce must be iterative as well to support the speed and evolution of responsible innovation.
AI leaders want to change the world for the better
Great leaders go down in history for making a substantial impact on the world. AI represents powerful technology that can be used for both positive and negative purposes. We need strong, powerful, service-driven leaders who aim to balance the benefits of technology with the benefit of society. We need strong leaders to push back on things that can be done by asking if they should be done.
Not every problem in the world can be solved by AI, just as not every problem in the world can be created by AI. We need AI leaders who will stand as a constant in the chaos. Those who look through hype to create visionary strategies that push the boundaries of what’s possible while simultaneously implementing realistic advances today. People who ask hard questions and demand alignment to an ethical framework.
Leaders who can inspire people to design a better future for all of us should be front and center of the AI evolution. If you’re ready to step up, the AI field needs your leadership.
About the Author
Mary Beth Ainsworth is an AI and Language Analytics Strategist at SAS. She is responsible for the global SAS messaging of artificial intelligence and text analytics. Prior to SAS she spent her career as an intelligence analyst and senior instructor in the US Department of Defense and Intelligence Community, primarily supporting expeditionary units and special operations.
- Article Analytics leads to lifesaving cancer therapiesA long-shot treatment offers hope to 10-year-old Harrison after he learns the DNA profile of his cancer is resistant to chemo. Find out how data and analytics play a role in cancer research and cancer treatments that are saving lives.
- Article IoT: The customer experience accelerator you can't afford to ignoreIoT represents a powerful source of data that, when combined with analytics, can yield insights on everything from behavior to emotions to health. And that's why it's key to improving customer experience.
- Article What big data has brought to the privacy discussionHow does big data impact your privacy? There are ways to balance privacy and security in an increasingly transparent and dangerous world.
- Research Nerd in the herd: protecting elephants with data scienceA passionate SAS data scientist uses machine learning to detect tuberculosis in elephants. Find out how her research can help prevent the spread of the disease.