The Impact of AI in Modern Business: A Deep Dive into its Relevance for Vista Advisory
Artificial Intelligence (AI) has become one of the most transformative technologies of the 21st century, impacting life generally and the way we work with notable implications for the consulting and advisory (C&A) space. As with new technologies and innovation, AI offers tremendous potential for human advancement but also raises ethical concerns with its increasing adoption.
For instance, industry experts have raised concerns around the exploitation of AI for misinformation and its job displacement prospects. Nevertheless, one must be willing to bet on a positive correlation between the advancement of AI, optimized decision-making, and increased firm performance.
What is Artificial Intelligence? Artificial Intelligence refers to the simulation of human intelligence in machines to perform tasks such as problem-solving, learning, understanding of natural language, and pattern recognition for analysis and decision-making. A slight adjustment to this definition is where the contention originates. “Artificial Intelligence refers to the simulation of human intelligence in machines to perform tasks typically requiring human intelligence”. This begs the question: Is human intelligence losing its relevance? And more seriously, am I losing my relevance? This is the anxiety of the proliferation of AI, and this is no different at Vista Advisory.
Vista is an organization that prides itself on staying at the forefront of technology and innovation. We recently launched our proprietary data intelligence platform Vista IQ which owes a significant part of its present operations and future potential to the capabilities of AI, so we embrace that the future is here and engage with it to remain competitive.
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There is endless literature on the benefits of AI, but our focus is finding an effective transition and collaboration between a learning organization (Vista) and a learning algorithm (AI) such that the algorithm does not consume the organization. This challenge is better understood by enunciating the nexus between the culture of a learning organization and its value proposition.
A learning organization stands on four pillars: First, it must imbibe a shared vision that learning is a strategic advantage. Second, at the center of its ethos must be a quest for personal mastery such that individuals understand that continuous self-improvement and skill development allow them to contribute their expertise effectively. Thirdly, seamless flow and sharing of information is encouraged, prioritized, and incentivized. Finally, it must be highly adaptable and responsive to change.
The unique and creative interaction of these four pillars is the human algorithm that forms the basis of our organization’s value proposition; it represents the dynamic ability to propose solutions that have not been tested before (mostly). If a transformer can achieve this in seconds, then we must adapt and optimize our approach to service delivery.
How are we adapting at Vista?
- Refocusing our delivery proposition and process more tightly to Acumen – a component that is less susceptible to a learning machine algorithm at least in the short term. Acumen in this context is the application of practical judgment to delivery. For example, the assumptions that go into building a financial model are judiciously prioritized over an associate’s dexterity and proficiency at using spreadsheets. Think garbage in, garbage out. For one thing, algorithms need human knowledge to provide accurate outputs.
- Strategic and gradual integration of AI into workstreams starting with areas where pursuance of personal mastery has much less future value. For example, drafting of memos, cover letters, introduction letters, etc.
- Upskilling to alleviate the ethical and adaptation challenges of introducing AI into the organization, these includes the effective use of AI to avoid plagiarism (adequate referencing where due) and a linear progression of staff ability to ensure job security.
Understanding the true influence of AI and formulating longer-term strategies that enable sensible choices in the contemporary business landscape should only be done based on a quantitative understanding of its impact that must be both relatively broad and sufficiently deep. Organization behavior that will arise as a result of AI efficiency should also not be ignored, it is sure to further advance the discourse between the mandate to increase shareholder earnings against corporate social responsibility. In the meantime, we can only hope that our reactions to AI will be sufficient to brace for its impact in the longer term.
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