Across the globe, organizations are trying to determine how they can use artificial intelligence (AI) to optimize growth and streamline processes. Some organizations are ahead of their competition when it comes to using AI in their operations.
The organizations that are maximizing their use of AI followed certain steps to achieve success. They didn’t just flip the switch and start realizing beneficial results. In this article, we will examine various stages of AI success and how Copilot for Microsoft 365 — an AI companion — can help organizations work smarter and be more productive.
It is important to adopt an AI-first strategy focused on delivering value-based use cases to the organization. This step is also essential to establish a future-proof target architecture for your enterprise as it moves along the AI readiness maturity scale. Using this approach, your organization can deliver tangible value early on while adopting an AI-ready culture. This helps to demystify AI in the hands of business and technical leaders. Implementing AI solutions for AI’s sake is not enough, value-led initiatives should be the priority to instill competitiveness and adaptability in this rapidly evolving landscape.
Exploring AI
Many organizations are in the early stages of exploring AI. Yet, they may be questioning the value of AI. A Gartner 2023 AI Use-Case ROI Survey points out that the “main barriers preventing implementation of AI are unable/hard to measure value and lack of understanding AI benefits and uses.” 19% of respondents cited “unable/hard to measure the value” and 19% cited “lack of understanding AI benefits and uses.”1
It’s important for organizations to experiment with AI for multiple reasons.
- Identifying opportunities: Experimenting with AI can help organizations identify new opportunities for improving efficiency, productivity and customer satisfaction
- Innovation: Experimentation is a key driver of innovation and AI presents significant opportunities for organizations to develop new products and services
- Competitive advantage: By experimenting with AI, organizations can gain a competitive advantage in their industry by being early adopters of new technologies
- Learning: Experimentation allows organizations to learn about the capabilities of AI and how it can be applied to their specific business needs
- Risk mitigation: By experimenting with AI on a smaller scale, organizations can mitigate the risk of large-scale investments in the technology
Experimenting with AI is a mandate but experimenting alone is not enough. A common occurrence is stopping at the crucial point of value creation or getting stuck in analysis paralysis. What does success look like? A tailored approach to testing your AI value-based hypothesis on your baseline is a necessary component commonly overlooked.
What Is Your Strategy?
To understand the benefits, organizations must define their business strategy for using AI. They need well-defined and prioritized business objectives, as well as use cases and a clear measurement of the value of AI. Organizations need to determine what specific goals they want to achieve with AI.
Knowing your technology strategy is an important step in the exploration process. To optimize outcomes, it’s important to have an architecture for AI-ready applications and data platforms, clearly defined parameters for deciding whether to invest in an AI solution and plans for hosting data and applications. Ask yourself the following questions:
- Is my infrastructure capable of securely and efficiently providing AI applications with access to large-scale data? Are additional investments necessary?
- Considering my highest priority use cases, should I opt to purchase, develop or upgrade AI applications?
- What factors should I consider when deciding between hosting data and AI applications on-premises or in the cloud?
Your chosen architecture will dictate the necessary technologies, whether to purchase pre-existing solutions, develop it in-house or combine both approaches.
Evaluating existing data is another important step and one that should be done early. Review the data that is currently available within your organization to determine whether it is sufficient for AI applications. If the answer is yes, then you’re ahead of the game.
AI governance is a key component too. AI can impact organizations in significant ways, and governance helps certify that it is used responsibly and ethically. AI governance enables data to be collected, stored and used securely and responsibly, protecting the privacy of organizations. Governance also helps organizations comply with relevant laws and regulations, reducing the risk of legal and financial consequences. Additionally, governance frameworks can help build trust and transparency around AI applications, which is important for both customers and organizations.
AI and Culture
Organizations can’t forget about the impact AI can have on culture. Here are just some of the impacts:
- Changing work: AI changes the nature of work by automating repetitive tasks and freeing up employees to focus on more complex and creative work
- New skills: As AI becomes more prevalent, organizations will need to develop new skills and competencies to effectively manage and use the technology, which could impact the culture of the workplace
- New job roles: AI can create new job roles, such as data scientists and machine learning engineers, which could have an impact on organizational structure and culture
- New business models: AI can enable new business models, such as predictive maintenance and personalized marketing, which could impact the culture of the organization and the industry as a whole
Trust
Another often overlooked component of AI in the organization is the establishment of trust in your AI systems and technologies. To achieve this, the governance mentioned above must prioritize transparency, explainability and decision-making criteria. Additionally, regular audits and assessments should be implemented to provide accuracy, fairness and ethical alignment. This mitigates concerns around bias and reliability.
The impact of AI on culture is complex and multifaceted. It will continue to evolve as the technology becomes more advanced and widespread. For AI to be successful in an organization’s culture, it must have support from leadership and a well-defined operating model. People also need to be trained on how to use AI. While AI is designed to automate tasks and make decisions, it still requires human oversight and intervention. People need to understand how AI works, its limitations and how to interpret its results to make informed decisions.
Delivering New Value
AI has immense value in today’s world as it can revolutionize various industries and solve complex problems in innovative ways. With AI, machines can learn and improve their performance over time, making them faster and more efficient.
Here are just some of the ways that AI can deliver new value to organizations:
- Increased efficiency: AI can automate repetitive tasks and processes, leading to increased efficiency and productivity
- Improved accuracy: AI can analyze large amounts of data and identify patterns that humans may miss, leading to more accurate results
- Enhanced customer experience: AI can be used to personalize marketing messages and provide 24/7 customer support, leading to a better customer experience
- Cost savings: By automating tasks and improving efficiency, AI can help companies save money on labor costs and reduce waste
- Innovation: AI can enable organizations to develop new products and services and create new business models that were not possible before
- Competitive advantage: Companies that use AI to optimize growth and streamline processes can gain a competitive advantage in their industry
AI has the potential to revolutionize the way organizations operate, leading to increased productivity, profitability and customer satisfaction. By leveraging the capabilities of AI, companies can unlock new value and stay ahead of the competition.
Getting Started With Copilot for Microsoft 365
Copilot for Microsoft 365 is a new AI-powered tool designed to help developers write better code more efficiently. It uses natural language processing and machine learning algorithms to provide suggestions and auto-complete code snippets based on the context of the code.
To use Copilot, you need an active Microsoft Enterprise Agreement (EA) with Software Assurance (SA) or a subscription to Microsoft 365 Enterprise. Copilot is available to organizations that meet certain eligibility requirements, such as having a minimum number of licensed users. The eligibility requirements can vary depending on the specific Copilot service you are interested in.
Once your organization is eligible to use Copilot, you can select a plan that meets your needs. The available plans can vary depending on your organization’s location and licensing agreement. Some plans may include services such as onboarding assistance, training and technical support.
Cherry Bekaert can work with you to determine which Copilot plan is best for your organization and help you optimize its benefits.
Why Cherry Bekaert?
Our real-time industry solutions offer guidance and tangible solutions using Microsoft products. Our solutions resonate with clients’ unique challenges and opportunities, delivering measurable outcomes in AI to create more efficiencies, fill skill gaps and bolster bottom-line results.
