Introduction

Click Rain was founded on innovation — with the vision to offer leading-edge services in digital marketing. That tradition of innovation continues today.

We aim to do the best work with the best team by using the best tools. Innovation, world-class quality, and a Midwestern work ethic are in our DNA. We live on the leading edge. We explore new territory, techniques, and tools with a drive for excellence and a spirit of adventure.

Our clients expect the best solutions to their marketing and communication challenges. Our team members deserve the best environment to thrive and grow. Creativity, curiosity, and technology allow us to deliver on those promises — to get Better Every Day.

New technology can change our work, whether by changing the industry landscape, the skills of our craft, or the standard of excellence we hold. We don’t lose our curiosity or sense of adventure in light of new technology — we explore, learn, and make thoughtful choices about how to incorporate new tools into our work.

These guidelines outline how we make choices about using artificial intelligence (AI) in our work, centering the creativity and innovation that have always been at our core.

Expanding Our Toolbox

AI is a tool in our toolbox. We choose when, why, and how to use it.

AI isn’t inherently good or bad — it’s a complex, multifaceted set of tools we can choose to use in ways that make our team better and deliver a better result to our clients. Every tool we use is used at our direction, with our expertise behind it. We choose when, why, and how to use these tools — any “good” or “bad” comes from us, not from our machines.

Read more: AI is a tool in the marketing toolbox (Sioux Falls Business)

We use the best tools for the job. Sometimes, the best tool may be AI-powered.

Tools are part of our craft — they’re used to make us better. To make the best work, we use the best tools. But different tools might be the best in different situations. Sometimes, the best tool is the fastest. Sometimes, the best tool is the one that produces the highest-quality outcome, even if it’s slower. Sometimes, it’s the tool that accomplishes a task with the most efficient effort or cost.

We’re a services-based business. Our job is to create the best work possible within the time and scope afforded by the client’s investment. The tradeoff between time and excellence has always been a challenge, regardless of AI — every project could be perfected infinitely in a world without constraints. But finite time and investment mean every project has a stopping point.

Sometimes, delivering the highest-quality work within our constraints requires specific tools; sometimes, the best tool may be AI-powered. In these situations, we may choose to use AI-powered tools when they help us deliver a better result.

Empowering Innovation

We use technology to reduce or eliminate repetitive, redundant, and energy-draining tasks.

Clients hire us to tap into our expertise, creativity, skills, and strategy. Time used on tedious tasks that don’t fall in those categories could be better spent, and it’s our obligation to be the best stewards of our time and our clients’ investment.

Technology affords us the opportunity to reduce mundane and repetitive tasks. It’s our responsibility and expectation to do so.

No individual or group owns innovation. Everyone is learning, growing, and finding new ways to excel in their craft.

Our Better Every Day mantra means we want and expect everyone on the team to explore, experiment, and educate themselves on the latest advances in their domain — including how new technology and AI intersect with their role.

Everyone explores ideas, investigates new opportunities, and shares learnings with their team or department. From there, our team leaders determine whether and how to incorporate new solutions into official processes.

Enabling New Solutions

For explorations, concepts, prototypes, or internal-facing deliverables, AI can be used when it leads to a better result for the client.

Projects might include a number of deliverables used as samples, speculative work, or proofs-of-concept — the “things before the thing.” We often use these pieces to help the client see a specific vision we have in mind. Getting client buy-in early on in the project helps us reach a better final result with less rework. If AI tools (including visual/image generation) can help us align or convey our vision, it benefits us to do so.

  • Example: We have a specific vision for an aspect of the moodboard. Rather than searching extensively for a partial-fit example, we might use AI to create a bespoke example that exactly captures our vision.

  • Example: A client needs more help understanding the storyboards. We might use AI to add more detail, motion, or visual steps that help us get client buy-in for our vision.

For outsourced components, AI-powered solutions can be used if the quality and cost are the same or better than the alternative.

Some projects require outsourced components we don’t create in-house, like voiceover or stock photos. In cases when we might otherwise use a third-party marketplace or vendor for these components, we may consider whether AI tools can provide a solution that’s the same or better quality, or a better project fit, for the same or lower investment. In these cases, we let clients know this tradeoff is being considered.

Tasks that are impossible without AI may be solved with AI, as long as its use follows the rest of these guidelines.

Some tasks are impossible because of constraints of time, technology, or investment. We try to account for this in the scoping process, but sometimes project specs or client expectations shift during a project or new ideas come up that could lead to a better final product.

If a situation arises where AI could potentially solve a project need that’s otherwise impossible — whether impossible outright or given the constraints at play — we use creative problem solving to explore solutions, including considering how AI tools might fit in (while staying aligned with these guidelines).

  • Example: We need a two-second B-roll clip for a video, but we only have a still image. Additional video footage is impossible given the time or scope, so we might use AI to create a two-second video clip from the still image.

  • Example: A client in a highly technical field has a robust, publicly available library of knowledge resources (e.g., blog, ebooks). Reading hundreds of pages of text is impossible given the time or scope, so we might use these resources to create an AI-powered knowledge base our team can query to gain targeted subject-matter expertise as needed.

Being People-Centered

If we use AI in the creation of final client-facing deliverables, our team is always in the driver’s seat.

Human creativity and expertise drive everything we make. When we use AI in client work, we do so with care and intention over both the inputs and outputs.

AI can be used in the creation of final client-facing work in two cases, as long as its use aligns with the rest of these guidelines:

AI outputs can be used when our team has created substantial inputs to steer or train the system under our direct guidance.

Some projects might call for AI-powered solutions where we may use substantial inputs created by our team (like our work, examples, proprietary process, or data) to build, steer, or train AI systems for specific purposes.

In these cases, AI may be used to analyze, augment, or automate our work, leading to outcomes that would otherwise be impossible or time-prohibitive.

  • Example: We create a proprietary process to compare a website’s sitemap with analytics about traffic to each area of the site. We might use AI to complete the data calculation and analysis.

  • Example: We create a campaign with 100 different assets across many sizes and versions. Instead of manually resizing and versioning every asset, we might establish the art direction and provide the copy and specs, then use AI to replicate across all 100 assets.

AI outputs can be used when they’re a small part of the final work (not the main project outcome) and meaningfully improve the final work in a way that wouldn’t otherwise be possible.

We may use AI to create components that go into the final work, as long as the main project outcome (what the client signed on for) is created by our team.

In these cases, AI may be used to create, extend, or manipulate small parts of the work that would otherwise be impossible or time-prohibitive, provided it meaningfully improves the final product.

  • Example: We sell a client a website. They ask us to populate the new site with AI-generated photos. We may do so, since the client hired us for a website, not a photo library. (If they had signed on for a photo library, we’d shoot real, original photos, since the photos would be the main project outcome.)

  • Example: We design an email, and our developers code it in modern, accessible, responsive HTML. Since email platforms often use outdated or inaccessible coding styles, we might use AI to adapt our code for email platforms to ensure the best compatibility.

  • Example: We write a series of web pages for a new site. We need a meta description for each page — a concise, machine-readable summary of the page content within a certain character limit. We may use AI to bulk-draft the meta descriptions from the content we wrote, since it’s a small piece that accompanies the final work.

It’s our duty to protect our team, no matter how AI might advance.

We protect and believe in our team. In a changing industry and technological landscape, our priority is navigating AI in ways that support and protect our team’s jobs. We’re a company where people can continually grow and thrive, where we invest in our team’s talent and potential. That doesn’t change, regardless of AI.

That said, our obligation to protect jobs extends only to our team. AI is predicted to impact the workforce in multiple ways in a variety of industries. We know that our ability to control these impacts starts and ends with our own team.

Ensuring Quality & Compliance

We and our clients should be aligned around AI use.

Alignment starts by sharing these guidelines at the beginning of a new client relationship.

Our clients have the final say over most project decisions. They hire us for specific services, but not necessarily specific workflows, so we can adapt our processes when needed, within reason. If we aren’t aligned (i.e., if a client’s desires for a specific process or deliverable don’t align with these guidelines), our team leaders determine the best way forward.

  • Example: A client requires no AI be used in any way, including for internal workflows. We may proceed with the relationship, acknowledging there could be impacts to budget and/or timeline based on these constraints.

  • Example: A client wants fully AI-generated assets as a primary feature of their final project. We may proceed with the relationship, but only after making the tradeoffs clear. (This wouldn’t decrease the project investment after the contract’s been signed.)

  • Example: A client wants us to host an AI-generated website they created. We’re likely not the right fit and wouldn’t proceed with the relationship.

Any client-facing AI outputs must meet the same quality standards as all of our work.

Our standard of excellence applies to everything we produce. AI is only part of our toolset when it leads to better work — not doing more, faster, at lower quality. We rigorously review any work with an AI component to ensure accuracy and quality.

We are transparent about our AI use and guidelines with our clients, contractors, and partners.

Transparency is key. Our team members, our clients, and our community should understand how we use technology in our work. Our AI transparency practices include:

  • These guidelines will be publicly available and shared directly with clients, contractors, and partners.

  • Any use of AI outputs in final client-facing deliverables will be clearly disclosed.

  • Any private material from a client, contractor, or partner may not be used for training external AI models without approval in advance.

  • Any AI edits on partner-provided material must comply with our approved partner agreements.

Safety, privacy, and compliance are critical. We review, select, and use AI tools in ways that protect clients’ brands and data as well as our own.

Paid workspace tools generally offer the best safety, privacy, and compliance — ensuring any data uploaded won’t be used for external training purposes and the technology provider won’t hold copyrights for any work output from the service.

We review new AI tool adoptions to verify the tools meet our requirements for safety, privacy, and compliance.