When businesses are thinking about AI, they are often daunted by the idea of an autonomous agent becoming part of their team.
What does that mean for the existing team structure? How will the agent be managed, adhere to the guidelines, and how will data be secure?
These are often the primary concerns we hear when speaking to businesses of all sizes about introducing agentic AI to their team.
We need to remove the fear and uncertainty from the process. Our key mission is connecting people and technology, and agentic AI is no different. Agents are going to be the red thread that runs through a business linking its people and technology together going forward.
How to build the red thread
Unlike other technological revolutions, introducing AI agents to businesses is no longer just the IT team’s responsibility. It needs to be a cohesive project touching every area of the business, from finance to HR to leadership.
Sharp’s research of 2,500 SMEs showed that 70% of senior management in Europe are using AI, compared to only 20% at junior level.
AI must be truly embedded in business philosophy, right from the high-level strategic decisions to every customer interaction. It is not an add-on, or a behind-the-scenes activity, but a true commitment to innovating at every step of operations.
True AI adoption means not trying to hide where AI is used, but openly communicating internally about how AI, and agents in particular, can make employees’ lives easier, turbocharge business growth and deliver best-in-class customer service.
Ready, steady, go
We’ve spoken often about the importance of workflow auditing before AI is brought onboard. But what happens next?
Once you have reviewed businesses processes and identified where AI can bring the most value, the experimentation process begins.
Start with the two-three identified strategic processes, whether that be revitalising current processes or building new ones where AI makes them now financially viable. This is where a technology partner, such as Sharp, can advise on the right AI solution to fit the process, whether that be creating a tailored agent purely for this application, or using a packaged agentic AI solution from partners like Microsoft.
It won’t be the same for each process; even within the same business, distinct processes need unique solutions. Our knowledge of the AI agents on the market, as well as deep expertise and experience across a wide range of B2B sectors, enables businesses to find the perfect match of technology and application for their business.
From financial reconciliation tools to templates for business development, to automating customer queries, there is already a huge wealth of both generative and agentic AI tools available. However, without the right approach and knowledge, it can seem like an impossible choice.
Three questions to ask yourselves when bringing in an agentic solution are:
- Is this an essential process, and what is its desired outcome?
- Does it fit into an existing category, or does it need its own tailored solution?
- How sensitive is the data being used, so what guardrails are needed?
Those responses will help guide you to the solution best suited to the use case.
Which model works best?
The last question, on sensitivity of data, is often the question that keeps business leaders up at night.
There are two options with AI: closed models, that are built in your own environment and taught using only information that you feed it from your own company. And open language learning models (LLM), which are the names you are most familiar with, that learn from the information you input and all data is public.
Retrieval-Augmented Generation, or RAG, is a model in which you train the LLM using information you feed it from your business. This can be a cost-effective way of creating a knowledge base which can assist your team easily. It is important that this is done in closed models, to keep data safe and secure.
We help companies understand which model works best for them, with both generative and agentic AI uses, to use the technology in the most effective way for their business.
Onboarding agents
Businesses always dedicate time, resource and attention to onboarding a new member of your team, so why would it be any different with agentic AI?
This is not an isolated technology entering the workplace. Agents work most effectively when they are centred within a workflow, team and business. Therefore, the more time you dedicate to introducing the agent to your business, to training it, and establishing a clear way of working, the more successful the agent will be.
The onboarding process will of course look different to a human team onboarding, because agents should always be human enabled. So, the best way to start is to involve the whole team in the training of the agent, in addition to their own AI training on how best to work with the agent. That way, it is clear that all decisions remain in human hands, and the agent is embedded in the teams’ way of working from day one.
Adapting digital experiences
It is undeniable that AI has completely revolutionised our way of working. But that shouldn’t invoke fear. Companies that take the leap of faith now will be rewarded in the long-term, by reaping the rewards of an extended team.
The mentality of AI agents becoming part of your team requires a mindset shift at all levels of your business. However, companies that truly implement this, through training, awareness and targeted implementation, will link their employees with technology to deliver real business growth.
We are on the edge of an exciting change, that will empower employees to step into the next generation of the workplace with more knowledge and tools available to them than ever before.
