AI Decision-Making: Where are we now?

You’ve probably heard about artificial intelligence and seen its impact develop over the years. After all, why not? By automating vital activities and equipment, evaluating big datasets, empowering robotics, and enhancing productivity and customer experience, effective AI may drive an organization’s success. With AI spending expected to increase by more than 20% annually, businesses must get the basic knowledge to make informed decisions regarding their AI life cycle when the time comes.


We wanted to get a sense of where AI is right now and how decision-makers in businesses and government organizations are thinking about it. What kind of investments are they making? What advantages and disadvantages have they encountered? What does the future hold for artificial intelligence? As a result, we polled roughly 1,000 decision-makers from businesses and government organizations and combed the industry for external data. Here’s what we learned and find out how you can implement it to your thinking:


The use of artificial intelligence is on the rise


The benefit of AI is recognized by decision-makers. According to research, 66% have already reaped major benefits from their AI technologies and ecosystems. Commercial leaders perceive more profit and revenue, while government agency decision-makers see faster progress toward their purpose and goals. Only three main AI-enabling technologies had the greatest impact: machine learning, computer vision, and natural language processing. 


Bottom Line: AI is expected to play a larger role in operations and business models in the future, according to decision-makers and industry analysts, with a five-year CAGR of 32.7%. If you haven’t already begun your AI adoption journey, now is the moment to lay the groundwork and start integrating AI into your strategic and tactical business goals.


Data is still an issue


Analyzing massive datasets and discovering patterns is the most typical method that businesses use AI and benefit from it. Using data to its greatest potential, however, remains a hurdle. Our respondents claimed their companies either lack critical data inputs or don’t have a defined data acquisition and access plan. 


Bottom Line: Take on this issue right away and start gathering, cleaning, and storing your data in various formats and locations that your data scientists can access. If that isn’t an option, think about how you can gather or acquire the data you’ll need to get started with your top-priority use cases.


Trust is difficult to come by


AI continues to face cultural barriers. According to PwC research, 72% of organizations employing AI believe it will make their jobs easier in the future, while 63%  of consumers believe it will solve complex problems. According to our survey, nearly two-thirds of decision-makers (64%) claim their organization’s employees still don’t trust (or comprehend) AI-enabled advice. This lack of trust may be linked to automated analysis issues. 


Bottom Line: Begin with lower-risk AI applications that have a smaller impact in terms of scale and volume. Quick wins can help you develop confidence and trust in your organization’s procedures and tools, leading to increased adoption.


Safety is a top priority


Security concerns (such as remote access, hacking of AI technology, and data poisoning) are becoming more common across all commercial sectors and levels of government. 

Bottom line: Models are fragile and can be tampered with, causing model projections and, as a result, your actions to be influenced. Ascertain that you are completely aware of your risks and that adequate security policies are in place to safeguard your data, apps. 


The participation of external partners is crucial


Organizations and decision-makers invest in AI in a variety of ways, including collaborating with external suppliers and AI experts, making strategic hiring, and training current staff. However, most decision-makers think that working with external organizations to create AI skills is more cost-effective than building an internal team.


To deploy effective technology on time, more sophisticated enterprises, in particular, appreciate the value of collaborating with external vendors. Working with an external partner resulted in an average savings of 35% of the total expense. 

Bottom line: As businesses seek to fast adopt AI technology, external providers with best-of-breed solutions may be able to help them achieve differentiation and competitive advantage more quickly.


The status of artificial intelligence is robust, active, and increasing


It’s clear: today’s decision-makers are under pressure to determine which technological solutions, including AI, are best for their organization’s future. The pressure is increased by the need to get started. Any firm can move closer to realizing the business benefit of AI at scale by aligning tech investments with essential business objectives and choosing a plan or partner to manage your AI life cycle and interact with your data pipelines and front-end applications.



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Lovy Jain

Lovy Jain

Lovy Jain is a seasoned technology writer with over 7 years of experience. She is a software engineer who regularly collaborates with various organizations globally to write on the latest issues and topics pertaining to software products, solutions and services.

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