Businesses used every tool at their disposal, including AI, to solve difficulties and service consumers securely and effectively as the pandemic wreaked havoc on the world last year. While each company will require its own playbook to recover from AI’s wrath and maximize its investment in the technology, a thorough strategy should incorporate the following five elements:
A strategic investment in data
Data is the connective tissue and raw material of AI in a digital organization. Clean, machine-digestible data labeled by subject matter experts is required for AI models to be trained. They need a data storage infrastructure that spans organizational boundaries and provides data fast and reliably. As soon as the models are deployed, a data collection strategy and approach are necessary to train and tweak them on a regular basis.
A long-term AI strategy guided by the business
Culture and employee upskilling
AI agendas will struggle to acquire traction without employee buy-in and a culture dedicated to AI’s success. To acquire your employees’ commitment, you must first offer them with a basic grasp of the technology and data, as well as the benefits it will bring to them and the company. Upskilling the workforce is also critical, particularly in cases where AI will take over or enhance their current roles. If an organization focuses on a data-driven culture and a greater grasp of artificial intelligence, it will be easier to scale and succeed.
A commitment to ethical and unbiased use of AI
AI has a lot of promise, but it also has the potential to cause harm if companies use it in ways that customers don’t like or that discriminate against certain groups of people. Every company should create an AI ethics policy that lays out clear boundaries for how the technology will be used. This policy should include procedures to check for errors and imbalances in data, detect and quantify unintended bias in machine learning algorithms, track data provenance, and identify personnel who train algorithms as part of the DevOps process. Organizations should keep an eye on their models for bias and drift, and ensure that model decisions are explained.
How things will unfold
In the next two years, different industries will have different goals for investing in AI. Healthcare executives intend to concentrate their efforts on robotic tasks, telemedicine, and patient care. According to the corporation, AI will be utilized in life sciences to uncover new income opportunities, reduce administrative costs, and analyze patient data. Executives in the federal government say they want to improve process automation and analytics, as well as manage contracts and other responsibilities.
Furthermore, industry-specific demands vary. Retail leaders believe that customer intelligence, inventory management, and customer service chatbots will have the greatest influence. Industrial producers comprehend it in terms of product creation, engineering, maintenance, and production, to name a few. In addition, financial services companies expect to improve their fraud detection and prevention, risk management, and process automation.
AI will play a crucial role in eliminating fraud, waste, and abuse in the long run, as well as assisting businesses in optimizing sales, marketing, and customer service. Finally, we believe that AI will aid in the resolution of fundamental human concerns such as disease detection and treatment, agriculture and world famine, and climate change.
It’s worth working towards a future like that. Both the government and industry can help by working together to design guidelines that foster the ethical advancement of AI without choking the current wave of invention and excitement.