The blog series "Crossing the AI Chasm" aims to identify in practical form, critical actions organizations must take in order to fully and successfully integrate AI into their day-to-day operations.
Incorporating GenAI into your business’ operations is not a fad. It's a must. If you are not planning on doing it, at least do your team a solid and plan your business exit proactively. The questions is not “should we us AI”, but rather “what kind of AI, and how do we need to implement it?”
Whether you're looking to streamline workflows, enhance customer engagement, or drive efficiency, no AI matters until and unless we focus first on solving business problems and support strategic business goals.
Let’s start there, and consider these four suggestions to select the type of AI that your business needs:
Start with your strategic business plan
If you don’t have a current business plan with established goals, please click “like” before you close your browser. The rest of the blog matters not.
Focus on the initiatives that have the greatest impact
With your strategic business plan in hand, identify those initiatives and processes that handle 80% of the critical goals your business must accomplish. Look at those first with an aim to eliminate inefficiencies and then to streamline or redefine current processes.
Identify Inefficiencies and Bottlenecks
The first step in process evaluation is to identify inefficiencies that may be slowing down operations. These can manifest as repetitive tasks, data entry errors, or slow decision-making due to a lack of real-time information. Common bottlenecks often occur where manual processes intersect with the need for quick, data-driven decisions. By spotting these inefficiencies, businesses can target areas where AI can make a tangible difference.
Map Out Processes for AI Integration
Once you have identified the inefficiencies, the next step is to map out your business processes in detail. This involves creating a visual representation of each step in a process, the stakeholders involved, and the information flow. Key areas where AI can streamline operations include data analysis, customer service, inventory management, and predictive maintenance.
In mapping out processes for AI integration, consider complexity, volume and frequency:
The complexity of the task: Can AI simplify or automate it?
The volume of data involved: Can AI handle and analyze large datasets more efficiently?
The frequency of the task: Would automating this task with AI save significant time?
Map the business initiatives and processes to the correct form of AI
With initiatives and processes identified, and further qualified as candidates for AI, THEN you can move out to think what kind of AI is the one best for the job.
Conduct a Needs Analysis
Gather input from various stakeholders, including management, employees, and customers. This holistic approach ensures that the AI solution addresses the needs across the organization. Key areas to focus on include:
Process efficiencies: Where can AI streamline workflows, reduce errors, or speed up operations?
Customer experience: How can AI enhance customer interactions or provide more personalized services?
Data utilization: Are there untapped data sources that AI can analyze for insights
Competitive advantage: In what areas can AI provide a unique edge over competitors?
The needs analysis should result in a prioritized list of requirements that will guide the selection of AI technologies.
Match Needs to AI Solutions
With a clear understanding of the business needs, it's possible to explore the vast landscape of AI solutions. For example, a need for improved customer service may lead to the implementation of AI chatbots, while a requirement for better data insights might point towards machine learning algorithms for predictive analytics. It's essential to match each identified need with an AI solution that has a proven track record of addressing similar challenges.
Here is a link to a blog in the series where we describe the types of AI and the problems that they are best at solving. - LINK
Here is a comprehensive list of GenAI and use cases - LINK
Bonus: Think “Integrate” vs. “Use” and also “ Buy vs. Make"
Reviewing your business plan, identifying the critical processes and determining which AI solutions can make a positive impact to improve your odds of corporate success is very likely to give you a “you bet, let’s use AI!” answer.
That said. it is critical to distinguish “subscribing” and “using” an AI services vs. “integrating” and “implementing” AI enabled processes. One of the greatest challenges of new technology is that teams focus on “cool” and “shiny” features, and look at the business impact as a secondary objective. Always lead with solving a business problem, not just using a neat new technology.
The greater challenge in adopting AI in your business will be crossing the proverbial “theory to practice” bridge. How do we deploy the technology and do so in a way that operations are least negatively impacted? Who is best equipped to do that work? If your business is to benefit from the AI form(s) you end up using, the technology should be imperceptible to the user and seamless to the process it powers.
Free advice - trying to implement AI organically and by individual department is likely to frustrate your teams, and put all initiatives at risk.
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