If you are thinking about productivity you must be thinking about AI.
With the emergence of AI into our life his immediate impact was on the customer journey.
The current state of implementing AI for customer journey is very local as a plug-in for replacing human repetitive tasks, by doing that we are missing AI’s real potential.
AI true potential lies with the amazing opportunity he brings to build a cross bord beginning to end customer experience machine.
That can widely impact our understanding and ability to address our customers’ needs.
I think the biggest shift we need to make is not seeing AI as a tool which is how it is currently being viewed.
Why?
As this shift will enable us to have a bigger vision to the output we are looking to get from our AI investment.
What is the difference between implementing a tool to implementing AI?
Implementing a tool and implementing AI are two distinct processes, and their objectives and complexities differ significantly.
Here are the key differences:
Purpose :
Implementing a Tool:
The purpose of implementing a tool is usually to perform specific tasks or functions efficiently. Tools are designed to simplify and automate manual processes, improve productivity, and achieve specific outcomes.
Implementing AI:
The purpose of implementing AI is to enable machines or systems to perform tasks that typically require human intelligence. AI aims to mimic human cognitive abilities, such as learning, reasoning, problem-solving, and decision-making, to improve processes and make intelligent predictions.
Scoop:
Implementing a Tool:
Tools usually have a narrow scope and are designed to address specific needs or challenges within a particular domain or process.
Implementing AI:
Implementing AI involves a broader scope as it encompasses a wide range of applications and potential use cases across various industries and domains.
Complexity :
Implementing a Tool:
Integrating a tool into existing workflows is often straightforward and involves minimal complexity, especially if the tool is well-established and user-friendly.
Implementing AI:
Implementing AI can be more complex, as it requires developing or deploying machine learning models, natural language processing algorithms, or other AI techniques. Training AI models and ensuring they produce accurate and reliable results can be challenging.
Data Dependency:
Implementing a Tool:
Tools may require data input, but they typically do not depend heavily on large datasets or complex data processing.
Implementing AI:
AI’s effectiveness often relies on extensive and high-quality data to train models and make accurate predictions. Access to relevant and diverse data is essential for successful AI implementation.
Learning and Adaptation:
Implementing a Tool:
Regular tools do not learn or adapt on their own. They perform predefined functions and do not evolve over time.
Implementing AI:
AI has the ability to learn from data and improve its performance with experience. Machine learning algorithms, for example, can continuously update and adapt their behavior based on new data.
Impact:
Implementing a Tool:
Tools can have a significant impact on efficiency and productivity but may not fundamentally change the way a business operates or revolutionize processes.
Implementing AI:
AI has the potential for transformative impact, as it can revolutionize entire industries, disrupt traditional workflows, and lead to innovative solutions and business models.
From Me:
Implementing a tool focuses on enhancing specific tasks or processes to address individual departmental needs.
However, implementing AI goes beyond this; it involves harnessing the power of machine intelligence to achieve more extensive objectives, solve complex problems, and drive innovation and transformation across an organization or industry.
By envisioning AI as more than just a tool, we open ourselves up to a grander vision of what we can achieve.
In the initial stages, even if we implement AI primarily as a tool, to test partnerships or set up a playing ground, it lays the foundation for greater possibilities.
Holding this vision from the beginning allows us to maintain a long-term perspective on where we’d like to see AI in the future.
Without this guiding star, we might find ourselves starting over from scratch. So, having this perspective upfront enables us to plan for a future where AI plays an integral and expansive role.