What comes to your mind when you hear the term Artificial Intelligence (AI)? For most people, it conjures up an image where humans coexist with highly intelligent, human-like robots in a utopian (or dystopian) world – one that probably looks like their favorite AI book or movie. While this is too futuristic, AI has already penetrated and is impacting our daily lives in visible and invisible ways.
We often are reminded of the famous successes in AI gaming, where machines beat world champions in Othello, chess, and Jeopardy, to name a few. While these victories and the human-like robots tend to align with the sci-fi version of AI, let’s look at how these AI-gaming programs succeeded:
In gaming, where rules are limited and controlled, the time and resources that go behind these successes are phenomenal. Business, on the other hand, is uncertain, diverse, inconsistent and cannot be conducted under a fixed set of rules. Most importantly, businesses do not operate in isolation and must be agile to embrace dynamic global changes.
Despite the rise of AI and its impact both on personal and business fronts, what has been achieved so far falls under artificial narrow intelligence (ANI), performing a single task with expertise. Sounds underwhelming? The good news for businesses: we can start utilizing AI to get significant value – from increased revenue, efficiency, and optimized costs to improving decision making, creating new markets, and implementing innovative business models.
Here’s how you can leverage AI, from being innovative showcase projects by technology experts, to taking the center stage in business:
For AI to succeed, business stakeholders and leaders must have awareness trainings to gain a realistic understanding of AI – how it works, its potential and limitations. AI at scale is not about taking a big bang approach but involves ongoing stakeholder collaboration with the potential to change the company’s DNA.
In this journey, involve stakeholders at every point– outlining AI objectives, choosing use cases, considering ethical implications, identifying biases, changing business processes, and making course corrections. Senior leadership should spearhead this journey with AI-driven insights as aide, enabling them to make critical business decisions.
About the author:
Sasirekha Rameshkumar is a Transformation Consultant with over 25 years of experience in mainframes, J2EE, IT management, performance management, enterprise architecture and digital transformation. She has managed large projects and consulting engagements for clients in the USA, the UK, Switzerland, Malaysia, Singapore, and India. She is interested in tracking technology trends – AI, IoT, Blockchain – and applying them in solving business problems and reshaping the future of business. Sasirekha’s current focus is in the area of Enterprise AI Adoption exploiting technology leaps in NLP, Voice, Vision, ML and AI.
LinkedIn: www.linkedin.com/in/sasirekha-rameshkumar
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