Enterprise AI automates low-level tasks, freeing employees to focus on more valuable work. It also fosters decision-making, reduces risk, and helps businesses gain a competitive edge.
Implementing Enterprise AI solutions requires a systematic process to prove and deliver business value incrementally. This includes establishing a scalable backlog and creating a framework for governance.
1. Increased Productivity
The productivity gains from enterprise AI solutions are often a primary reason for adopting such technologies. Many AI applications automate mundane tasks, relieving teams from rote work and freeing them for more meaningful activities.
This translates into increased departmental efficiency, from streamlining data management to enhancing human decision-making. For example, image recognition software and predictive analytics in supply chain management allow businesses to see trends and patterns that manual inspections may miss.
Another area where artificial intelligence improves efficiency is in the hiring process. AI software streamlines screening calls eliminates bias in job candidate assessments, and reduces hiring time by analyzing application responses faster than humans can. This increases the chances of finding top talent while eliminating costly hiring mistakes.
One of the benefits of Enterprise AI is that it helps companies make better decisions by generating actionable insights that assist with planning, risk assessment, and new business models. As such, these solutions help businesses achieve ROI with the potential to boost revenue, cut costs, and reduce risks.
2. Increased Customer Satisfaction
AI applications help businesses meet customer expectations in speed, personalization, and monitoring. For example, streaming media services use intelligent systems to study consumer buying patterns and larger data sets to create hyper-personalized products, services, and content recommendations. Retailers use intelligent systems to understand purchasing trends and forecast demand, resulting in improved inventory management and pricing decisions.
Additionally, AI software can make it easier for teams to complete tasks that are usually difficult to do manually. By reducing the number of manual tasks that teams are bogged down with daily, they can focus on important work like improving the customer experience and marketing initiatives.
Additionally, AI solutions that automate repetitive tasks increase office morale and allow employees to complete more critical projects that require human creativity or attention to detail. These AI tools also eliminate roadblocks that can impede workflows by centralizing, unifying, and simplifying information for easy access and distribution. For example, some provide a low-code workflow builder that allows teams to create digital representations of physical processes for automation with enterprise AI.
3. Increased Revenue
Media and entertainment leaders realize the high stakes of AI adoption, but getting alignment across organizational departments is a significant hurdle. When CIOs and technical decision-makers are the only ones involved, a lack of visible results can stall a project.
Fortunately, the best enterprise AI solutions are designed to deliver concrete business benefits. Visual reports summarizing behemoth amounts of information speak to logistics management and reveal predictive insights programmed to outperform human data analysts.
These insights are powerful at content production’s pre-production and post-release stages. At the pre-production stage, predictive AI models can project audience demand and revenue potential to expand profit margins and mitigate risk. Distribution teams can use predictive AI to anticipate the market by platform, audience segment, and release date to maximize licensing terms.
Some companies even go as far as leveraging their enterprise AI solutions to take action, allowing for customer-facing automation. For example, it uses a 3-1-0 model, processing loan applications in three minutes and one second with zero human intervention. This dramatically reduces the administrative burden on employees and frees them to focus on other pressing tasks.
4. Lower Costs
The technology requires new skills that some organizations may still need to gain, which can mean hiring or upskilling current staff to meet business needs. The costs of hardware, software, and other IT infrastructure can also be significant.
Companies can also save on labor and operational costs by using AI to automate repetitive tasks, enabling employees to focus on more complex and critical work. This is common for customer support departments where AI can help reduce ticket volume and improve the quality of service by routing and addressing simple questions quickly.
AI also helps organizations accelerate their business processes, increasing efficiency and potentially opening up new revenue streams. Retailers use it to analyze large data sets to improve sales forecasting, optimize supply chains, and develop new product offerings.
5. Increased Competitiveness
Enterprise AI is a powerful technology that can help companies gain competitive advantages by increasing efficiency and productivity, reducing costs, and improving customer service. However, it can take time to implement correctly. Many projects fail to produce meaningful results and can be costly in both time and money.
Companies must ensure their AI efforts align with business goals to reduce risk. Choosing a vendor that can deliver precise, understandable results and minimize the amount of human interaction required is also essential.
Some of the most effective solutions incorporate conversational interfaces, leveraging natural language processing to answer real-time questions. One example provides a knowledge base and helpdesk and the ability to connect with an organization’s entire tech stack via API integrations.
For example, in highly competitive fields with small talent pools, AI can speed up hiring processes by automating first-round screening calls and analyzing candidate applications at a rate far faster than humans can. In addition, it can eliminate human bias from initial assessments and enable more diverse workplaces.
Financial firms can use it to enhance credit scoring and fraud detection. Companies that deploy AI for risk management can predict potential security risks and automate a response, saving time and money. For example, an AI solution that pairs machine learning with industrial IoT sensors could prevent workplace accidents by predicting and warning of environmental hazards or unsafe conditions.