A staggering $15.7 trillion. That's the potential contribution of applied AI to the global economy by 2030, according to a recent study by PwC.
This figure underscores the immense power of AI to reshape industries and revolutionize business practices. But with such an opportunity comes a series of questions: Is your organization harnessing the potential of AI, or is it falling behind in an increasingly competitive marketplace? Is it doing so in an orderly and planned manner?
This guide provides a practical framework to navigate your way through the application of artificial intelligence. By leveraging Gartner’s AI Opportunity Radar, you'll gain the tools to assess your current state and define your ambitions and implementation feasibility. You'll also learn how Acid Labs can help you with your AI adoption strategy. Let's get started!
Where does your organization fall on the AI adoption spectrum?
AI adoption is not a one-size-fits-all approach; organizations take various approaches depending on their business goals, resources, and level of technology maturity. Identifying where your organization falls on this spectrum can provide valuable insight into your AI readiness.
1. Productivity pursuers
These organizations prioritize AI solutions that augment and automate tasks in some front and back-office functions. They seek moderately sustainable competitive advantage through incremental productivity and operational efficiency improvements. In addition, they are exploring using AI at the core of their business to improve day-to-day operations and drive transformational change in their industry.
2. Not in front of my customers
These organizations are more cautious in their approach to AI. They primarily focus on improving internal operational efficiency (back office) and core capabilities. They have no immediate plans to implement AI in customer-facing applications (front office).
3. AI first/everywhere
At the other end of the spectrum are the organizations that take a bold and proactive approach to AI. They see AI as a strategic tool for innovation and disruption and actively explore opportunities in all business areas, both in customer-facing applications and internal operations.
What is your organizational ambition?
Your organization's ambition in the AI adoption process is to understand where and how you will use artificial intelligence to achieve your business goals. In essence, you are charting the course of your strategy.
Gartner's AI Opportunity Radar provides a valuable framework for visualizing this ambition. It focuses on two key axes:
1. Where AI will be deployed (vertical axis).
● Will it be used to improve internal operations, such as data analytics or workflow automation?
● Will it be customer-facing, transforming the customer experience through AI-powered chatbots or personalized recommendations?
2. How AI will be used (horizontal axis).
● Everyday, productivity-focused AI: This category includes AI solutions that act as digital assistants, automating repetitive tasks and augmenting human skills. These solutions offer quick wins that can increase overall productivity and efficiency.
● Game-changing, creativity-focused AI: This category goes deeper to drive innovation and transformation. It enables you to create entirely new products and services, or even transform your business model. It has enormous potential to give you a competitive advantage but is much more costly and risky.
In addition, the radar provides a visual representation of four potential quadrants:
■ Front Office (customer-facing): This quadrant focuses on using AI to improve customer interactions. For example, it can be used in customer experience, sales, marketing, and customer service.
■ Products/Services (AI-driven value creation): This area focuses on developing AI-enhanced offerings and exploring entirely new AI-driven products and services.
■ Back Office (operational efficiency with AI): This area focuses on using AI to streamline internal processes. Automating repetitive tasks with AI-powered tools or using AI to analyze data fall into this category. For example, it can be used in administration, human resources, legal, IT, and finance.
■ Core Capabilities (AI-driven innovation): This area explores the use of AI to transform the core operations of your business. Examples include AI-driven supply chain management or research and development (R&D).
How feasible is an AI implementation?
Organizational ambition is just one piece of the puzzle. You also need to determine how feasible it is to implement different AI solutions.
The three concentric rings of the AI Opportunity Radar represent the levels of feasibility of different AI solutions. These rings consider three key dimensions:
■ Technical feasibility: Can your organization acquire and implement the technology?
■ Internal readiness: Is your organization open to and capable of deploying AI solutions?
■ External readiness: Will your customers, partners, and other external parties accept AI?
Combining these dimensions results in an overall feasibility score:
■ High feasibility (inner ring): The technology is readily available, relatively inexpensive, and integrates well with existing workflows. This makes it easy for employees to adopt it. These solutions have a low barrier to entry and are a good starting point, but may not provide a significant competitive advantage.
■ Medium feasibility (middle ring): The technology is less mature and typically more expensive. Some organizations, especially early adopters, may choose this type of solution.
■ Low feasibility (outer ring): The technology is unproven and requires significant effort to convince employees, markets, and partners of its value. Only the most competitively aggressive organizations seeking industry disruption will venture into this arena.
Want to implement or improve your AI adoption strategy?
Gartner's AI Opportunity Radar provides a valuable framework for understanding your organization's ambitions for applied artificial intelligence and assessing the feasibility of different solutions. However, translating this knowledge into practical strategies can be challenging. This is where Acid Labs comes in.
At Acid Labs, we understand the challenges organizations face when trying to integrate applied AI into their processes. That's why we help you deliver real value to your business. How do we do this?
■ Optimizing operational efficiency: We use AI to identify areas for improvement and automate processes, enabling our clients to operate more efficiently and flexibly.
■ Reducing costs: Our AI solutions are designed to maximize ROI by reducing operational costs and eliminating process redundancies.
■ Improving decision-making: With advanced data analytics and predictive modeling, we provide our customers with valuable information to make more informed and strategic decisions.
■ Predicting market trends and behavior: Using machine learning techniques, we help our customers anticipate market trends and adapt quickly to changes in demand and competition.
Our operating model
At Acid Labs, we take a collaborative and consultative approach to implementing AI solutions. We combine our expertise in applied artificial intelligence with data engineering capabilities and work on AI data readiness, i.e. preparing and optimizing data so that it is in an optimal state to be used by AI models.
Our delivery model is highly flexible and customizable. We offer a variety of solutions, from proof-of-concepts (PoCs) and prototypes to quickly validate ideas and proposals, to pilots and minimum viable versions (MVPs) for larger-scale implementations.
We can even combine these stages into a single AI-Driven Value Team. AI Data-Driven Teams combine multiple AI initiatives in sync with our clients' business strategies and AI ambitions.
Benefits of an AI-Driven Value Team
By choosing an AI-Driven Value Team, you can expect numerous tangible benefits:
■ Save time and effort: We simplify the AI implementation process and optimize resource allocation to maximize efficiency and minimize costs.
■ Synergistic initiatives: Our collaborative approach ensures that all initiatives are aligned with business strategy and mutually beneficial.
■ Risk mitigation: Our team has extensive experience implementing AI solutions in various industries, enabling us to identify and mitigate potential risks from the outset.
■ Quality assurance: From initial discovery to final delivery, we are committed to delivering the highest quality AI solutions that drive value and innovation for your business.
At Acid Labs, we are here to help you take your AI adoption strategy to the next level. Contact us today!
