One of the most inter­est­ing qual­i­ties about AI tech­nol­o­gy is that the ben­e­fits are vir­tu­al­ly lim­it­less. Near­ly every indus­try stands to gain in some way from the pow­er of machines, and this tech­nol­o­gy is just as rel­e­vant to con­tent mar­keters as it is to the most com­plex tech com­pa­nies.

How­ev­er, it seems that the inte­gra­tion of AI and mar­ket­ing is only begin­ning to grow. Today, near­ly 40% of mar­ket­ing depart­ments report that they are adopt­ing AI into their strate­gies, and the major­i­ty do believe that the tech­nol­o­gy could make pos­i­tive improve­ments to their tac­tics.

Although AI tech­nol­o­gy has near­ly end­less amounts of poten­tial for ALL busi­ness oper­a­tions, there is clear evi­dence that it can be espe­cial­ly use­ful for con­tent mar­keters. If your mar­ket­ing depart­ment is weigh­ing the options of how it could ben­e­fit from AI, or is look­ing for inspi­ra­tion on where to begin, here are three clear-cut areas where this tech­nol­o­gy can sup­port a strong con­tent strat­e­gy.


Ideation is nev­er easy. Year after year, the process of cre­at­ing engag­ing con­tent is report­ed as mar­keters’ top chal­lenge. This is espe­cial­ly true for brands that focus on curat­ing con­tent for top­ics that require intense research and knowl­edge.

The key to stay­ing rel­e­vant in the ever-increas­ing noise of the echo cham­ber is by pro­vid­ing mean­ing­ful and rel­e­vant insights, mak­ing bold claims, and show­cas­ing exper­tise. With AI tech­nol­o­gy, con­tent mar­keters have access to data reports that can guide their ideation and cre­ation process­es so each piece of con­tent is high­ly tar­get­ed to the core audi­ence.

AI sys­tems like can help sup­port a more strate­gic cura­tion process by ana­lyz­ing audi­ence sen­ti­ment to under­stand the sub­jects and nich­es that pique their inter­est.

AI-based pre­dic­tive analy­sis sys­tems can cal­cu­late audi­ence reac­tions and sen­ti­ment with var­i­ous top­ics to give con­tent mar­keters a feel for which sub­jects will gain the most trac­tion. Data-dri­ven tools can also pro­vide reports in regards to shifts in the mar­ket that could sig­nal top­ics that will soon gen­er­ate buzz.

The insights from AI sys­tems can then be used to cre­ate high-val­ue con­tent assets, such as tuto­ri­als, whitepa­pers, webi­na­rs, and long-form con­tent. These types of thought-lead­er­ship assets are heav­i­ly based in research and can be espe­cial­ly influ­en­tial for build­ing brand trust, cred­i­bil­i­ty, and even increas­ing con­ver­sion rates. Fur­ther­more, these assets can be used as a rev­enue stream. For exam­ple, you can repur­pose the con­tent as an eBook to sell on your web­site.

By using AI-assist­ed data, cre­ative and mar­ket­ing teams can craft mes­sag­ing that match­es up with what their ide­al cus­tomers are look­ing for.


Cre­at­ing con­tent that is spe­cif­ic to each view­er has been a top pri­or­i­ty for many mar­keters as of late, but the exe­cu­tion of this process is often quite dif­fi­cult. In order to imple­ment effec­tive per­son­al­iza­tion, teams must have access to loads of con­sumer data which must be prop­er­ly ana­lyzed and trans­lat­ed into action­able strate­gies.

While per­son­al­iza­tion has been a mar­ket­ing buzz­word for many years, recent advance­ments in AI tech­nol­o­gy are final­ly mak­ing this con­cept a full-blown real­i­ty. Machine learn­ing sys­tems are able to gath­er rel­e­vant data points from web­site vis­i­tors and cus­tomers. From here, they can build indi­vid­ual pro­files that can be used to cre­ate brand expe­ri­ences tai­lored to each per­son. Tools like OneSpot use AI-based algo­rithms and web inter­ac­tion data to ana­lyze engage­ment and match con­tent to indi­vid­ual pref­er­ences.

Cus­tomized offers and rec­om­men­da­tions are in high demand among con­sumers, as 80% revealed they would be more like­ly to pur­chase from a com­pa­ny that offers per­son­al­iza­tion. By using AI-enabled soft­ware to track each customer’s behav­iors and pref­er­ences, brands can use this infor­ma­tion to guide their con­tent strate­gies through mul­ti­ple approach­es, includ­ing cus­tomized con­tent that is spe­cif­ic to each cus­tomer, as well as send­ing indi­vid­u­al­ized offers for high­er con­ver­sions.

Real-time engagement

The nature of con­tent mar­ket­ing these days is very inter­ac­tive. If a user has a ques­tion or wants more infor­ma­tion, they should be able to get in touch with a brand instant­ly. One of the eas­i­est ways to turn new, poten­tial, and exist­ing cus­tomers off is by mak­ing it hard to get in con­tact. For this rea­son, many com­pa­nies are using appli­ca­tions like AI-pow­ered chat­bots to learn about the type of queries peo­ple have, for­mu­late appro­pri­ate respons­es, and in some cas­es, make sales.

Data-dri­ven chat­bots use machine learn­ing to track and ana­lyze each con­ver­sa­tion and make improve­ments with every inter­ac­tion. Due to its abil­i­ty to learn and adjust to meet each customer’s needs around the clock, chat­bots receive high­er engage­ment lev­els than any oth­er tac­tic. In fact, 60% of con­sumers state that they would glad­ly inter­act with a chat­bot in order to get an answer to a ques­tion or to resolve an issue.

Even though chat­bots have only been around for a few short years, the ben­e­fits are more or less uni­ver­sal among con­sumers.


AI-pow­ered sys­tems and data-dri­ven tech­nol­o­gy allows mar­ket­ing teams to meet their goal of cre­at­ing more rel­e­vant, high-qual­i­ty con­tent. Mar­keters can also use AI to gain the prop­er insights to cre­ate mes­sag­ing tai­lored to each viewer’s pref­er­ences. More­over, they can have auto­mat­ed chat­bots to help peo­ple every step of the way.

AI is expect­ed to trans­form much of what con­tent mar­keters are able to do by sup­port­ing each step of their strate­gies with data. By imple­ment­ing this kind of tech­nol­o­gy into these impor­tant aspects of con­tent mar­ket­ing, busi­ness­es are in a much bet­ter posi­tion to place the right con­tent in front of the most inter­est­ed eyes.