ONBOARDING AI
Meet Albert Irving
To you, a robot is a robot. Gears and metal; electricity and positrons. Human-made! If necessary, human-destroyed! But you haven’t worked with them, so you don’t know them.”
Isaac Asimov
Isaac Asimov’s book I, Robot pushed the concept of “robot” into our cultural consciousness back in the 1950s. One of the most interesting ideas in the book are the “three laws of robotics” that lay out how humans and robots could conceivably live together in harmony. Throughout the book (which is a series of short stories), Asimov brilliantly teases out all of the nuances and loopholes that can crop up in and around prescribed laws. Even with the laws of robotics in place, humans and robots have to learn to live and work together: it requires a level of cooperation on the part of the humans to integrate these helpmates into their usual routines.
With the advent of AI, we find ourselves at a watershed point in history in terms of the potential for machine and human intelligence to work together. While some still regard AI with concern, the truth is that it was created to act as a team-member who brings a diverse skill set to the table: it isn’t meant to take over the jobs humans do best. The sooner organizations allow themselves greater receptivity toward this incredible innovation, the sooner they will avail themselves of higher levels of collaboration and output.
Today we’re going to imagine a day in the life of Albert Irving – Al, for short – a new hire at a business who’s looking to expand its team with a robot colleague.
AI’s first day: The onboarding process
It’s Al’s first day on the job. Understandably, he’s nervous, and so are his new human colleagues. Although the team was prepped with information about Al before his arrival, reactions are mixed.
The content director, is resistant to handing over any element of his process – is Al here to erase his role as a writer?
The marketing strategist, feels cautiously optimistic: maybe Al will help her and John collaborate more effectively on campaigns by keeping things more organized and by helping with projections — but what if he brings a robotic chill to the workplace?
The IT specialist, is excited. He’s been advocating for integrating advanced technology like Al for years and is eager to see the kinds of improvements Al might bring in data security and system efficiency.
The client relations manager, is curious to see if Al is good with clients when it comes to handling basic queries and data input, possibly allowing her more time to build stronger connections with customers in situations where empathy and patience are needed.
Al’s onboarding unfolds similar to any new employee. First, there’s the initial setup, which involves preparing a dedicated server to host Al, allowing him to interact with existing systems.
Following the setup, Al is integrated into the company’s IT system. He receives secure connections to the internal network, and APIs are created to enable him access to data across departments, effectively plugging him into the company’s main operating system.
Al’s access to data is carefully managed via specific permissions set according to Al’s job functions, granting him access to only the essential information needed for his tasks – nothing more, nothing less. Al is also programmed to comply with relevant data protection standards.
AI settles in: Daily operations
Getting comfortable in a new job takes time for most of us, and Al is no different. But bit by bit, as Al becomes more immersed in the company’s daily operations, his role begins to be more clearly defined, and his value starts to shine through to his colleagues.
For John, the content director, and Laura, the marketing strategist: John is starting to see the value AI brings when it comes to data analysis and content optimization. Al’s ability to efficiently tag and classify a huge array of content, from text to images to videos, is making John’s job of organizing and finding content many times easier. This in turn helps Laura tailor her marketing campaigns more precisely: Al’s ability to rapidly sort through and organize user data and generate reports on various performance KPIs is second to none.
Far from taking John’s place as a writer or usurping Laura as a strategist, Al shows himself to be a humble and efficient assistant who takes care of the grunt work, helps keep things easily accessible, and provides keen insights they otherwise might have missed.
For Mark, the IT specialist: The more he works with his new colleague, the more he enjoys him. Al’s capability to monitor network security and automate system updates is particularly helpful. The moment Al spots a vulnerability or potential threat, he alerts Mark, allowing Mark to address issues before they become a liability.
Rachel, the client relations manager, is thrilled with Al. He automates the initial stages of client interactions by taking on routine questions (leaving the more complex interactions to Rachel). Al also keeps track of client data, making sure every interaction and all feedback is recorded and organized. This helps enrich client profiles and gives Rachel the necessary information and context so that she can engage on a more personal level.
Enhancing collaboration across the organization with AI’s help
Now that Al has effectively gotten his feet wet and become familiar with operations across teams (and now that his new colleagues have warmed up to him), he’s eager to prove his mettle as a team member who fosters cross-departmental collaboration within the company.
The company is working on a promotional campaign for a client that requires close collaboration between the content, marketing, and client relations departments. The campaign involves an enormous amount of information and has a lot of moving pieces, and getting all of these elements to work together effectively has been a point of contention amongst the teams in the past. Here’s how Al helps along each step of the process.
Content and Marketing Departments
John leads the content team in creating engaging material with a specific audience in mind, and Laura then guides the marketing team’s efforts in designing effective campaigns and building out a launch strategy. Al helps the teams work together by providing data-driven insights on relevant topics, audience sentiment, and engagement metrics. He also looks over past campaigns and how they performed in order to identify predictive patterns. Then, with that information in mind, he advises the teams on how they can adjust the content and hone in on marketing channels that might increase reach.
Client Relations
Al helps Rachel keep the client in the loop regarding the campaign by sharing progress reports and updates, and gathers insights from the client’s responses which helps her address any changes or concerns the moment they arise.
Al shows himself to be an excellent, well-informed, neutral communicator – which is exactly what the company has needed!
He automatically updates all teams with real-time data and client feedback, helping everyone stay on the same page, and preventing the old habit of siloing that has kept the teams at odds in the past. His ability to log and track every modification and suggestion regarding the campaign in real-time helps team members maintain accountability and transparency, and this enhanced awareness helps remove tension-inducing ambiguity around the rationale behind decisions and their role in the collective goal.
Assessing AI’s performance
Just like with any employee, Al will be assessed on several key performance indicators (KPIs) to gauge his impact within
the organization.
Process efficiency
Al was brought on to help streamline routine tasks across departments, such as data entry, scheduling, and report generation. By automating these tasks, the hope is that Al will free up team members to focus on complex tasks involving strategy or client interaction. This KPI is measured by observing the reduction in time employees spend doing administrative work.
Decision-making enhancement/cross-team collaboration
Prior to Al’s onboarding, the content and marketing teams were struggling with cross-collaboration. The hope was for Al to provide more points of connection and shared information between the teams, ultimately allowing for quicker, more deeply informed strategizing on campaigns and other client projects. Al has accomplished this by offering both teams quick access to relevant data and analytics, leading to an overall increase in the efficiency and quality of the decisions made across various departments.
Client satisfaction and engagement
Al assists in managing client relationships, with the goal of improving client satisfaction through personalized and prompt responses. His performance here is measured by feedback from clients and the level of engagement with the content and services provided.
Overall, Al has done extremely well in his first three months on the job. His performance will undergo ongoing assessment based on preset KPIs and colleague feedback, as this helps the company maximize his capabilities and identify areas for improvement.
The verdict: when to promote, demote, or fire AI
Deciding whether Al’s role within the team is beneficial for the long term involves careful evaluation of his performance against set expectations and goals. Here’s how the company can determine the potential outcomes of promotion, demotion, or termination.
Promotion
If Al consistently exceeds his key performance indicators and works well with his colleagues, that’s a good sign that his capabilities can be expanded. Promoting Al could involve granting him more responsibilities or integrating him into additional departments where his skills can offer similar benefits.
Demotion
A demotion might be necessary if Al meets some, but not all, of his objectives (or if certain processes do not go as planned when given to his care). This doesn’t automatically mean Al should be let go, but that it may be wise to develop a performance improvement plan and restrict his role until issues are resolved. This period can be used for recalibration and further training to enhance his algorithms, particularly in areas where his performance has been lacking (for example, when handling complex client queries).
Termination
If Al doesn’t meet most of the outlined KPIs and his integration into the company results in no measurable improvements (or worse, a decrease) in operational efficiency or client satisfaction, it may be time to consider termination. This kind of decision should be based on a thorough analysis of costs vs benefits and whether the technology has potential for improvement or if it is fundamentally unsuited for the company’s particular set of needs.
As we look back over Al’s journey of integration into the company, we can see clearly that the successful collaboration between humans and AI hinges on the right conditions and an open approach. This partnership, when properly implemented and managed, can lead to significant advancements. Just as in Asimov’s vision, the interaction between human creativity and machine intelligence as experienced in Al’s story illustrates the fact that artificial intelligence isn’t meant to replace human processes, but rather to support and augment them.
