How to Choose Brand Colors with AI

Generating a color palette with AI usually starts from one of two inputs: a text description of mood or tone, such as 'calm and professional' or 'playful and energetic,' or a reference image whose color relationships the AI tool extracts and adapts. Either way, the output is a starting set of candidate colors, not a finished brand palette, because two steps still need human judgment: accessibility and role assignment. Accessibility checking means verifying that any color pairing used for text against a background meets a recognized contrast standard, most commonly the Web Content Accessibility Guidelines, which define minimum contrast ratios for text to remain readable for people with low vision or color-vision deficiencies. An AI-generated palette that looks visually pleasing can still fail this check; a light gray on white, or colors with insufficient light-dark contrast, may look fine to someone with typical vision but be very hard to read for others. Several free contrast-checking tools exist specifically for testing a foreground and background pair against these standards. Role assignment means deciding, in advance, what each color in the palette is for: a primary color for main branding and buttons, an accent color used sparingly to draw attention, and neutral colors for backgrounds and body text. Without this step, a team ends up picking colors ad hoc for each new piece of content, undermining the consistency a palette is meant to provide. Do not treat an AI palette as automatically final or accessible. Check the combinations actually used for text, controls, and backgrounds, and add labels or other cues where color communicates meaning. A contrast calculation answers a specific contrast question. A color-vision simulation approximates some viewing differences, but cannot prove how every person will perceive the design. Save the approved combinations and their intended uses so later editors do not accidentally substitute an untested background.