Twitter, now X, has become more than just a social media platform. It has become a digital town square, a place where ideas are debated at lightning speed, and trends are born within seconds as global conversations are held about major topics. But even as this vast, opinions-and-news stream races by, one underlying force is shaping that experience: the growth of AI and automation.

From bots whose purpose is to propagate messages at scale to the algorithms that choose what content to display on your feed, automation has become part of Twitter’s fabric, in both an advantageous and harmful way, given that it raises fundamental questions about authenticity, trust and the value of human voices in a space that is becoming more and more influenced by machines.

How bots are informative in going, and alterations in the discussion

Indeed, for years now, social media platforms have been turned into bots for purposes ranging from sharing political propaganda to brand marketing and notifying users of upcoming news, weather, and stock market updates. In fact, many bots serve a legitimate purpose and, all preferences considered, a helpful purpose (e.g. reminders to drink water, price notifications for cryptocurrency, or archiving tweets before they are washed away.) In fact, these utility-based accounts improve user experience and make the site more enjoyable to use.

Specifically, there are an increasing number of damaging or misleading bots that are used to clutter conversations, purposely influence trending topics, or blatantly misinform followers.

For example, during various political campaigns, there are many documented cases of bots being intentionally used to pump up hashtags to make it seem like there was public support (or outrage) when it was in fact, a manufactured public sentiment.

This purposely creates a misrepresentation of public opinion, thereby muddying the waters for users to directly differentiate between authentic conversations and engineered discussions.

Verified Voices and the Quest for Authenticity

The use of bots and bots detected, at the same time, Twitter developed verification and the blue checkmark became the small badge of a user who had been verified at least for identity. For at least a decade, verification was available only for public figures, journalists, and organizations in a public status speaking not for personal, but for social good. It indicated that an individual could speak with authority, as an academic or as a recognized source.

Over time, the blue checkmark evolved in its meaning. With the expanding non-reasonable and unreasonable paid verification subsystems, membership for many is literally just dollars. In this light, verification became accessible to everyone in a number of membership plans, of which the blue badge was part of a program consistent with Twitter’s design.

In today’s digital information age, however, it also made the meaning of verification light and diluted its originally intended meaning. Users seem to second guess every account that is verified. In part a user questions whether it was a credible source deserving of verification, or a user simply willing to pay for status.

AI Drives Content Discovery & Reach

Aside from escalating bot usage and verifying accounts, AI is also a driver of Twitter’s recommendation algorithms. For example, recommendation algorithms determine which tweets show up in users’ feeds, which conversations trend, and which tweets gain attention. While recommendation algorithms can be useful and even help to discover relevant content, they often create opportunities for manipulation and bias.

For example, if engagement is the sole metric of preference, even if a tweet is wrong or not reputable, it might be picked up more if it achieves a higher level of engagement. Not only does this exaggerate a story, it also reaffirms outrage and polarizing narratives, leaving behind discussions which could remain nuanced.

AI enabled recommendations could even help smaller voices to find discoverability, thus creating opportunities for niche creators to achieve larger audiences without a large following.

Balancing Act of Automation and Human Interaction

The biggest challenge for Twitter lies finding balance between automation and authenticity. Automation is necessary to achieve scale; platforms need automation to moderate content, identify harmful behaviour and personalize experiences for millions of users. However, when too much is automated, Twitter risks putting itself at risk of being a platform that is dominated by bots, algorithms and artificially constructed narratives.

The right story, authentic reaction, or unique perspective resonates with audiences in a way that is impossible for a bot to replicate. This is also why authentic people are becoming the currency for Twitter; the audience is looking for real voices to cut through the noise of automation, providing clarity, relatability, and trust.

The Way Forward for Authenticity on Twitter

Looking down the road, we will likely see a greater role for automation and AI on the Twitter platform. The advent of generative or intelligent AI means bots will be even more capable of mimicking human behaviour, tone, and even emotions, making it more difficult than ever for users to differentiate real people from automated accounts.

As automation and AI continue to permeate the social media landscape, transparency and accountability will be particularly important for Twitter. This will require rigorous labelling of automated accounts, improved identity verification systems, and better detection measures for automated accounts. More importantly, users themselves will determine the future of authenticity. If users display themselves as engaged stakeholders and hold brands and influencers accountable for their credibility and authenticity

Conclusion

AI and automation have changed Twitter in undeniable ways, influencing how conversations happen and how content spreads, as well as authenticity. Bots and algorithms can provide great efficiency and scaling but can also make it hard to distinguish between real engagement and artificial influence. The authentic voice is still the strongest influence in this context.