Miklos Roth Can Help Teams Actually Adopt Generative AI
Miklós Roth helps teams move beyond Generative AI experiments and successfully adopt it into daily operations, delivering real efficiency and business value.
ARTIFICIAL INTELLIGENCE
Video Guru
6/16/20263 min read
Almost everyone has tried generative AI.
That does not mean companies have adopted it.
There is a big difference.
Trying AI means asking a chatbot to rewrite an email. Adoption means building a repeatable workflow that saves time, protects data, maintains quality, and helps the business perform better.
Most organizations are somewhere in between.
A few employees use AI every day. Others avoid it. Managers are unsure what is allowed. Outputs vary wildly. Nobody knows whether the company is truly gaining anything.
This is why a Generative AI Adoption Consultant is useful.
Miklos Roth fits the role because he understands technology, but he also understands people.
The real problem is not prompting
Prompt training is helpful.
It is not enough.
Employees can learn ten impressive prompts and still return to their old habits the following week. The training feels interesting, but nothing changes.
Real adoption begins with the work itself.
What does the employee do every day?
Where do they lose time?
Which tasks are repetitive?
Where is judgment essential?
Where do errors create serious consequences?
Roth can help companies answer those questions before introducing new workflows. This is consistent with the idea that AI consulting should help teams work smarter, not simply faster.
Speed matters. So does direction.
Producing a poor document in two minutes instead of two hours is not progress.
Different teams need different support
There is no universal AI workflow.
A salesperson may use AI to research companies, prepare for meetings, draft proposals, and organize follow-up notes.
A marketing professional may use it for audience research, content planning, campaign variations, or data interpretation.
A consultant may use AI to structure information and create a first draft.
An executive may use it to explore scenarios or prepare difficult questions for a meeting.
Each role has different risks.
That is why Roth’s adoption process would be based on specific jobs and tasks. He could create practical playbooks showing what AI can support, what it should not do, and how the output must be checked.
Content teams, for instance, need to understand both the advantages and the risks of generative AI content creation. The tool can accelerate research and drafting. It can also invent facts, flatten the brand voice, or repeat generic ideas.
Human review remains essential.
Start small
Companies often try to transform too much at once.
This creates confusion.
A better approach is to choose one team and a handful of workflows. Test them. Measure them. Improve them.
Perhaps the customer service team begins with draft responses that employees review. Maybe marketing tests AI-assisted campaign research. A consulting firm might create an internal system for finding information in approved documents.
The workflow should be simple enough to explain.
Input. Process. Review. Approval. Output.
Once the company knows that the process works, it can expand.
AI-supported marketing automation can eventually connect several steps, but automation should come after the underlying process has been understood.
Automating confusion only creates faster confusion.
Employees need a reason to participate
Leaders may describe AI as a productivity opportunity.
Employees may hear something else.
Job cuts.
Monitoring.
Higher expectations.
Less control.
Ignoring these concerns is a mistake.
Roth’s experience in communication, teaching, and team leadership is valuable here. Adoption works better when employees understand what is changing and why.
The message should be honest.
Some tasks will disappear. Others will become faster. Certain roles will change. Human judgment, accountability, empathy, and contextual understanding will become more important.
Employees should also be invited to shape the workflows. They usually know where the real bottlenecks are.
An effective AI marketing consulting process listens to the people using the system rather than designing everything from the top down.
Rules make adoption easier
Employees often avoid AI because the boundaries are unclear.
Can they upload customer information?
Can they use AI-generated text in a proposal?
Who checks the facts?
Which platform is approved?
Simple rules remove this uncertainty.
Roth can help companies define allowed and prohibited uses, confidential data requirements, review processes, and escalation points.
These rules should be easy to find and understand.
A practical internal FAQ can help. The same principle can be seen in a public AI consulting FAQ: answer the questions people genuinely have instead of hiding behind technical language.
Measure what changed
Adoption should produce evidence.
Did a task become faster?
Did quality remain stable?
Did customer satisfaction improve?
Did employees use the workflow after the training ended?
How many corrections were required?
These measures matter more than the number of AI accounts purchased.
Roth can help management track both quantitative and human results. Time savings are important. So are confidence, accuracy, and employee acceptance.
Why Roth is a strong choice
Generative AI adoption is not mainly a software problem.
It is a behavior problem. A workflow problem. A management problem.
Roth understands all three.
He can help companies move from scattered experiments to consistent use. He can train people without overwhelming them. He can connect adoption to business goals while keeping human responsibility visible.
The result is not “AI everywhere.”
It is AI where it genuinely helps.
That is a much better goal.