What Bachelor’s Degree is Best for a Career in AI?

If you’ve been con­sid­er­ing an AI bach­e­lor degree, you might won­der which major would work best for you. While machine learn­ing is inte­gral to under­stand­ing how AI works, it isn’t the only major that can set you up for a lucra­tive career in arti­fi­cial intelligence.

Read on to learn more about which degree is best for AI and how to get into AI. Our ana­lysts have con­sult­ed the most accu­rate, up-to-date data. 

Which Degree Is Best for AI?

There are now schools that offer arti­fi­cial intel­li­gence majors. How­ev­er, you can also take an inter­dis­ci­pli­nary approach if you want a more well-round­ed back­ground. For exam­ple, three majors pro­vide essen­tial skill sets required for machine learn­ing jobs.

Con­sid­er the fol­low­ing arti­fi­cial intel­li­gence degrees based on your goals and interests:

• Com­put­er Science
• Data Sci­ence
• Robot­ics

Busi­ness ana­lyt­ics, math­e­mat­ics, and oth­er degrees also give you the fun­da­men­tals need­ed to suc­ceed in an arti­fi­cial intel­li­gence career. Here’s a deep dive: 

Computer Science

Com­put­er sci­ence is the most pop­u­lar AI bach­e­lor degree. A Com­put­er sci­ence AI bach­e­lor degree pro­gram will include cours­es that cov­er algo­rithms, data struc­tures, pro­gram­ming, and AI-relat­ed hardware/software. Above all, you’ll need pro­gram­ming skills to under­stand and adapt algo­rithms, which are the core ele­ments of arti­fi­cial intel­li­gence. You must also under­stand data struc­tures to make them more effi­cient and accu­rate. Com­put­er sys­tems store a lot of data, but not all of it is valu­able. For­tu­nate­ly, a degree in com­put­er sci­ence will give you the core under­stand­ing need­ed to devel­op and improve AI algo­rithms for var­i­ous industries.

Data Science

A data sci­ence AI bach­e­lor degree teach­es you how to make bet­ter pre­dic­tions. As a data sci­en­tist, you will devel­op mod­els that ana­lyze data and make valu­able pre­dic­tions. Machine learn­ing based on faulty data isn’t very valu­able. How­ev­er, arti­fi­cial intel­li­gence makes it eas­i­er to sep­a­rate use­ful infor­ma­tion from raw data that can quick­ly become over­whelm­ing. Beyond that, too many erro­neous dat­a­points can skew the results of deep learn­ing sig­nif­i­cant­ly. There­fore, data sci­en­tists hold a crit­i­cal role. A bach­e­lor’s degree in this field will focus on sta­tis­tics, com­put­er sci­ence, and mathematics.

Robotics

Robots no longer exist only in the imag­i­na­tion of sci­ence fic­tion writ­ers and movie mak­ers. Today, robot­ics deals with the phys­i­cal man­i­fes­ta­tion of AI sys­tems. From build­ing cars to per­form­ing phys­i­cal tasks too demand­ing or dan­ger­ous for humans, robots may hold a key place in every­day liv­ing in the not-so-dis­tant future. An AI engi­neer degree in robot­ics will give you the knowl­edge nec­es­sary to enhance the per­for­mance and intel­li­gence of self-reliant robot­ic sys­tems that observe and react to the envi­ron­ment around them. 

Data Analytics

What can you do with a data ana­lyt­ics degree? First­ly, it can pro­vide the infor­ma­tion you need to jump­start a career in arti­fi­cial intel­li­gence. Start­ing with a firm foun­da­tion in ana­lyt­ics, you’ll find it eas­i­er to under­stand and manip­u­late large data sets. Addi­tion­al­ly, you’ll learn how machine learn­ing works and take part in improv­ing it. As the capa­bil­i­ties of sys­tems and machines advance, it’s essen­tial to con­sid­er eth­i­cal issues. For exam­ple, good data sci­en­tists under­stand the impor­tance of prac­tic­ing fair­ness, respect­ing pri­va­cy, and safe­guard­ing human rights.

Machine Learning

An AI degree in machine learn­ing includes a firm com­put­er sci­ence foun­da­tion and advanced train­ing in arti­fi­cial intel­li­gence. Arti­fi­cial intel­li­gence is often used syn­ony­mous­ly with machine learn­ing. How­ev­er, machine learn­ing is a sub­set of AI. It focus­es on min­ing data sets for infor­ma­tion that can improve algo­rithms. In many cas­es, this cen­ters around a spe­cif­ic task. Even­tu­al­ly, you may find your­self build­ing pro­grams that make it eas­i­er for com­put­ers to process and respond to dif­fer­ent situations.

Business Analytics

As a busi­ness ana­lyt­ics pro­fes­sion­al, you may find your­self act­ing as a bridge between AI experts and key mem­bers of your orga­ni­za­tion. Busi­ness ana­lyt­ics would com­bine an AI bach­e­lor degree with busi­ness knowl­edge. One of the pri­ma­ry rules for those who work in busi­ness ana­lyt­ics involves the respon­si­ble adop­tion of AI. Besides, you’ll need a firm grasp of cus­tomer needs, mar­ket dynam­ics, and busi­ness and a deep under­stand­ing of machine learning.

Mathematics

With­out math, com­put­ers would­n’t exist. AI degree pro­grams require a firm grasp of math­e­mat­i­cal con­cepts. So, if you love math and are good at it, a math­e­mat­ics degree could be a great approach to gath­er­ing the knowl­edge you need to suc­ceed in the AI field. Care­ful­ly review the cur­ricu­lum to ensure your cho­sen pro­gram focus­es on AI top­ics. For exam­ple, you’ll need cours­es incor­po­rat­ing sta­tis­tics, algo­rithms, and com­pu­ta­tion­al methods.

Statistics

Sta­tis­tics involves col­lect­ing and ana­lyz­ing a large amount of data. With a degree in sta­tis­tics, you’ll devel­op essen­tial skills for machine learn­ing. AI uses sta­tis­ti­cal method­ol­o­gy to pre­dict and mim­ic human behav­ior in dif­fer­ent sit­u­a­tions. Like a math degree, a sta­tis­tics AI bach­e­lor’s degree will expose you to com­put­er sci­ence and oth­er skills need­ed to land an arti­fi­cial intel­li­gence job.

Engineering

Self-dri­ving cars, drones, robots, and oth­er devices come from the minds of bril­liant engi­neers. With­in the realm of machine learn­ing, engi­neer­ing is con­sid­ered a sub­field. You’ll need to take cours­es and com­put­er sci­ence, AI, elec­tri­cal engi­neer­ing, and relat­ed sub­jects to com­plete an engi­neer­ing degree. 

Can I Work in AI with a Humanities Degree?

Yes, you can absolute­ly work in the field of arti­fi­cial intel­li­gence (AI) with a human­i­ties degree. While a back­ground in com­put­er sci­ence or an AI bach­e­lor degree is com­mon, the AI indus­try val­ues diver­si­ty and often wel­comes indi­vid­u­als with diverse edu­ca­tion­al backgrounds. 

What Can I Do in AI? 

Here are sev­er­al ways you can lever­age your human­i­ties degree to con­tribute to the AI field:

• Nat­ur­al Lan­guage Pro­cess­ing (NLP): Human­i­ties grad­u­ates often have a strong com­mand of lan­guage, mak­ing them well-suit­ed for roles involv­ing nat­ur­al lan­guage pro­cess­ing. NLP is a sub­field of AI that focus­es on the inter­ac­tion between com­put­ers and human lan­guage, includ­ing tasks like lan­guage trans­la­tion, sen­ti­ment analy­sis, and chat­bot development.
• Ethics and AI Pol­i­cy: The eth­i­cal impli­ca­tions of AI and the devel­op­ment of AI poli­cies are crit­i­cal areas where indi­vid­u­als with human­i­ties back­grounds can make sub­stan­tial con­tri­bu­tions. Com­pa­nies and orga­ni­za­tions are increas­ing­ly rec­og­niz­ing the impor­tance of eth­i­cal con­sid­er­a­tions in AI, and human­i­ties grad­u­ates can play a piv­otal role in shap­ing respon­si­ble AI practices.
• User Expe­ri­ence (UX) Design: Human­i­ties grad­u­ates often pos­sess strong cre­ative and crit­i­cal think­ing skills, mak­ing them valu­able con­trib­u­tors to UX design in AI appli­ca­tions. Design­ing AI inter­faces that are user-friend­ly and align with human val­ues is cru­cial for the suc­cess of AI systems.
• AI Jour­nal­ism and Com­mu­ni­ca­tion: There is a grow­ing need for pro­fes­sion­als who can com­mu­ni­cate com­plex AI con­cepts to diverse audi­ences. Human­i­ties grad­u­ates with strong com­mu­ni­ca­tion skills can work in AI jour­nal­ism, tech­ni­cal writ­ing, or as AI com­mu­ni­ca­tion spe­cial­ists, help­ing bridge the gap between tech­ni­cal experts and the gen­er­al public.
• AI in the Arts and Cul­ture: AI is increas­ing­ly being used in cre­ative fields, such as art and music. Human­i­ties grad­u­ates with an under­stand­ing of cul­tur­al and artis­tic prin­ci­ples can con­tribute to the devel­op­ment and appli­ca­tion of AI in cre­ative endeavors.
• Inter­dis­ci­pli­nary Research: Col­lab­o­ra­tive projects often ben­e­fit from indi­vid­u­als with diverse per­spec­tives. Human­i­ties grad­u­ates can col­lab­o­rate with com­put­er sci­en­tists and engi­neers in inter­dis­ci­pli­nary research projects that involve AI appli­ca­tions in areas like dig­i­tal human­i­ties, social sci­ences, or linguistics.
• Data Anno­ta­tion and Label­ing: Human­i­ties grad­u­ates with exper­tise in lan­guage and con­text can con­tribute to data anno­ta­tion and label­ing tasks, which are essen­tial for train­ing machine learn­ing mod­els. This involves cat­e­go­riz­ing and anno­tat­ing data to improve the accu­ra­cy of AI systems.

To enter the AI field with a human­i­ties back­ground, con­sid­er adding skills to your tool­box through online cours­es, work­shops, or spe­cial­ized pro­grams. Focus on areas like data sci­ence, machine learn­ing, or pro­gram­ming. Build­ing a port­fo­lio that show­cas­es your inter­dis­ci­pli­nary skills and col­lab­o­rat­ing with pro­fes­sion­als from diverse back­grounds can also enhance your appeal to employ­ers in the AI indus­try. Remem­ber, the AI field val­ues a com­bi­na­tion of skills and per­spec­tives, and a human­i­ties degree can bring unique insights to the table.

What are Some Other Ways to Get Into AI?

While a com­put­er sci­ence back­ground can cer­tain­ly pro­vide a strong foun­da­tion, the field of arti­fi­cial intel­li­gence (AI) is mul­ti­dis­ci­pli­nary, and pro­fes­sion­als from var­i­ous edu­ca­tion­al back­grounds con­tribute to its diverse land­scape. Here are sev­er­al path­ways for enter­ing the AI indus­try with­out a com­put­er sci­ence degree:

• Domain-Spe­cif­ic Exper­tise: If you have exper­tise in a spe­cif­ic domain (e.g., health­care, finance, or mar­ket­ing), com­bin­ing your indus­try knowl­edge with AI skills can make you high­ly valu­able in devel­op­ing AI solu­tions tai­lored to spe­cif­ic sec­tors. Even with­out an AI bach­e­lor degree. 
• Self-Taught and Boot­camps: In fact, many suc­cess­ful AI pro­fes­sion­als are self-taught or have com­plet­ed spe­cial­ized train­ing through cod­ing boot­camps, online cours­es, or AI-focused pro­grams. These options allow indi­vid­u­als to acquire prac­ti­cal skills and build a port­fo­lio of projects.
• Cross-dis­ci­pli­nary Degrees: Some uni­ver­si­ties offer inter­dis­ci­pli­nary pro­grams that com­bine ele­ments of com­put­er sci­ence, math­e­mat­ics, and oth­er fields. These pro­grams can pro­vide a well-round­ed edu­ca­tion suit­able for AI roles.

It’s impor­tant to note that in the AI indus­try, prac­ti­cal skills, expe­ri­ence, and a port­fo­lio of projects often car­ry sig­nif­i­cant weight. Employ­ers may pri­or­i­tize demon­strat­ed abil­i­ties and rel­e­vant expe­ri­ence over for­mal degrees. Build­ing a strong net­work, par­tic­i­pat­ing in AI com­mu­ni­ties, and con­tin­u­ous­ly updat­ing your skills can also enhance your prospects in the AI field. While a com­put­er sci­ence degree or AI bach­e­lor degree can open doors, it’s not the sole gate­way to a suc­cess­ful career in arti­fi­cial intelligence.

What is AI Anyway? 

Arti­fi­cial intel­li­gence deals with devel­op­ing soft­ware that thinks and hard­ware that makes it pos­si­ble. AI has been around for three decades, emerg­ing from inter­dis­ci­pli­nary coop­er­a­tion between neu­ro­science, elec­tri­cal engi­neer­ing, and com­put­er sci­ence pro­fes­sion­als, to name a few. Today, AI seems har­nessed only by the phys­i­cal lim­i­ta­tions of cur­rent hard­ware. With numer­ous appli­ca­tions putting machine learn­ing to work, AI tools are final­ly get­ting the com­put­ing pow­er required to use machine learn­ing on a large scale.

AI is now used in trans­porta­tion, health, man­u­fac­tur­ing, automa­tion, secu­ri­ty, and many oth­er areas. In the future, AI is like­ly to make many devices more capa­ble and effi­cient than ever. 

• Agri­cul­ture: You might be sur­prised to hear that agri­cul­ture uses AI. But pre­ci­sion agri­cul­ture employs AI for crop mon­i­tor­ing, yield pre­dic­tion, and opti­miza­tion of resource use. Drones and sen­sors equipped with AI assist in mon­i­tor­ing and man­ag­ing agri­cul­tur­al operations.
• Auto­mo­tive: In addi­tion, the auto­mo­tive indus­try uti­lizes AI for autonomous vehi­cles, pre­dic­tive main­te­nance, and smart man­u­fac­tur­ing. AI algo­rithms help vehi­cles per­ceive their envi­ron­ment, make deci­sions, and nav­i­gate safely.
• Cyber­se­cu­ri­ty: AI enhances cyber­se­cu­ri­ty by detect­ing and respond­ing to cyber threats in real-time. Machine learn­ing algo­rithms ana­lyze pat­terns to iden­ti­fy and pre­vent secu­ri­ty breaches.
• Edu­ca­tion: In edu­ca­tion, AI is used for per­son­al­ized learn­ing, auto­mat­ed grad­ing, and intel­li­gent tutor­ing sys­tems. It can adapt to indi­vid­ual learn­ing styles and pro­vide insights into stu­dent performance.
• Ener­gy: The ener­gy sec­tor uti­lizes AI for pre­dic­tive equip­ment main­te­nance, ener­gy grid opti­miza­tion, and pre­dic­tive ana­lyt­ics for ener­gy con­sump­tion pat­terns. AI also helps improve the effi­cien­cy of renew­able ener­gy sources.
• Enter­tain­ment: In the enter­tain­ment indus­try, AI is used for con­tent rec­om­men­da­tion, video and audio analy­sis, and vir­tu­al real­i­ty expe­ri­ences. AI algo­rithms per­son­al­ize con­tent deliv­ery based on user preferences.
• Finance: In the finan­cial sec­tor, AI is employed for fraud detec­tion, algo­rith­mic trad­ing, risk man­age­ment, cus­tomer ser­vice through chat­bots, and per­son­al­ized finan­cial advice. Machine learn­ing mod­els ana­lyze mar­ket trends and opti­mize invest­ment portfolios.
• Health­care: AI is used for diag­nos­tic pur­pos­es, per­son­al­ized med­i­cine, drug dis­cov­ery, and pre­dic­tive ana­lyt­ics. In addi­tion, it can ana­lyze med­ical images, assist in surgery, and improve patient care through data-dri­ven insights.
• Human Resources: AI aids in HR process­es such as tal­ent acqui­si­tion, employ­ee engage­ment, and work­force plan­ning. More­over, AI stream­lines recruit­ment through resume screen­ing and auto­mates rou­tine HR tasks.
• Man­u­fac­tur­ing: AI enhances man­u­fac­tur­ing process­es through pre­dic­tive main­te­nance, qual­i­ty con­trol, and sup­ply chain opti­miza­tion. Robot­ics and automa­tion pow­ered by AI improve effi­cien­cy and reduce errors.
• Mar­ket­ing and Adver­tis­ing: AI is used in mar­ket­ing for cus­tomer seg­men­ta­tion, per­son­al­ized adver­tis­ing, and data-dri­ven cam­paign opti­miza­tion. Nat­ur­al lan­guage pro­cess­ing enables sen­ti­ment analy­sis and per­son­al­ized con­tent creation.
• Retail: Retail­ers lever­age AI for demand fore­cast­ing, sup­ply chain opti­miza­tion, cus­tomer behav­ior analy­sis, and per­son­al­ized shop­ping expe­ri­ences. Also, chat­bots and vir­tu­al assis­tants enhance cus­tomer interactions.
• Telecom­mu­ni­ca­tions: AI is employed in telecom­mu­ni­ca­tions for net­work opti­miza­tion, pre­dic­tive main­te­nance, fraud detec­tion, and cus­tomer ser­vice automa­tion. It also helps man­age and ana­lyze large datasets for improved oper­a­tional efficiency.

AI bach­e­lor degree hold­ers will get a first­hand look at cut­ting edge trends, the­o­ry, and appli­ca­tions. You’re like­ly a good fit for the field if you’re inter­est­ed in AI tech­nol­o­gy, autonomous sys­tems, robot­ics, or relat­ed topics.

An AI bach­e­lor degree gives you the knowl­edge to devel­op AI agents and work on advanced the­o­ries and algo­rithms for data analy­sis and opti­miza­tion. Most impor­tant­ly, upon grad­u­at­ing, you’ll find many employ­ers val­ue data sci­en­tists who can help them keep up with the ever-chang­ing land­scape and how it impacts their businesses.

Is a Degree in AI Worth It?

From a finan­cial per­spec­tive, it’s cer­tain­ly worth­while to pur­sue an AI bach­e­lor’s degree. For many posi­tions, you may find that you need a master’s degree or high­er to suc­ceed in the field. For advice on how to get into AI, start with the fac­ul­ty at your favorite schools.

You don’t have to major in AI itself to get the edu­ca­tion you need to start an entry-lev­el posi­tion. Alter­na­tive­ly, you can also choose from relat­ed degrees such as math­e­mat­ics, sta­tis­tics, and busi­ness ana­lyt­ics. In fact, it’s always a good idea to pur­sue as well-round­ed an edu­ca­tion­al expe­ri­ence as possible.

Machine learn­ing has a great capac­i­ty to advance the human con­di­tion. More effi­cient sys­tems save mon­ey and time. In many ways, an AI career can have a pos­i­tive impact on soci­ety as a whole.

Is AI a Hard Major?

Arti­fi­cial intel­li­gence degrees involve sub­jects that many peo­ple find dif­fi­cult. This might be the right field for you if you excel at math, com­put­er sci­ence, and sci­ence. There’s cur­rent­ly a demand for pro­fes­sion­als with advanced skills. In many cas­es, com­pa­nies are will­ing to train exist­ing employ­ees to take on expand­ed roles in machine learning.

Machine learn­ing is a key ele­ment of arti­fi­cial intel­li­gence. Because machine learn­ing algo­rithms are heav­i­ly steeped in sta­tis­tics, you’ll need to under­stand com­plex math­e­mat­i­cal mod­els. You can start by mas­ter­ing alge­bra, cal­cu­lus, and prob­a­bil­i­ty, all of which are crit­i­cal for a career in AI.

In addi­tion, you’ll need a sol­id foun­da­tion in com­put­er pro­gram­ming to become a data sci­en­tist or AI devel­op­er. We high­ly rec­om­mend learn­ing as much about Python as pos­si­ble, includ­ing its libraries. This lan­guage has syn­tax that makes it eas­i­er to work with large datasets.

If you need to brush up your math skills, you can always take cal­cu­lus and sta­tis­tics cours­es pri­or to switch­ing to an AI major. You can take pro­gram­ming cours­es to see if you have a knack for it.

How Do I Get Into the AI Industry? 

AI degree pro­grams pre­pare you well for a career in edu­ca­tion, engi­neer­ing, busi­ness, and oth­er fields. It all depends on where you set your career goals. When it comes to arti­fi­cial intel­li­gence and machine learn­ing, an ever-increas­ing num­ber of jobs are avail­able. How­ev­er, you have to have the skills to match the demands of this chal­leng­ing career choice.

An AI engi­neer degree will teach you the pro­gram­ming skills to devel­op and train AI mod­els. Using machine learn­ing algo­rithms, you’ll devel­op a think­ing sys­tem with deep learn­ing capa­bil­i­ties. As a machine learn­ing engi­neer, you’ll deploy mod­els with sophis­ti­cat­ed algo­rithms designed to improve per­for­mance over time.

As a data sci­en­tist, you will col­lect and ana­lyze data. A big part of this job lies in iden­ti­fy­ing unus­able data that can skew results, neg­a­tive­ly impact­ing the accu­ra­cy of your pre­dic­tive mod­els. In addi­tion, data sci­en­tists build tools that pro­vide deci­sion-mak­ers with ana­lyt­ics need­ed to make deci­sions based on data.

You can also become a research sci­en­tist and work on prac­ti­cal appli­ca­tions for machine learn­ing. Nat­ur­al Lan­guage Pro­cess­ing and Com­put­er Vision tech­nol­o­gy focus on mak­ing machines smarter and bet­ter able to com­mu­ni­cate. If you’re look­ing for how to get into AI, there are many ways, includ­ing the exam­ples above.

What About the Job Market with an AI Bachelor Degree? 

The advent of arti­fi­cial intel­li­gence was a huge tech­no­log­i­cal advance­ment. It already touch­es many aspects of dai­ly liv­ing. Because AI will con­tin­ue to impact your pro­fes­sion­al and per­son­al lives, cer­tain priv­i­leges come from work­ing in the field. You can use your skills to improve sys­tems with tremen­dous poten­tial to change the world.

The job mar­ket for AI pro­fes­sion­als is con­tin­u­al­ly grow­ing, with a high demand for indi­vid­u­als skilled in arti­fi­cial intel­li­gence (AI) and relat­ed tech­nolo­gies. How­ev­er, please note that con­di­tions may have evolved since then, and it’s advis­able to check the lat­est sources for the most cur­rent information.

What Makes the AI Job Market Strong?

There are a lot of fac­tors mak­ing a strong job mar­ket for AI professionals:

• Indus­try Growth: The AI indus­try has expe­ri­enced sig­nif­i­cant growth, with appli­ca­tions across var­i­ous sec­tors such as health­care, finance, e‑commerce, and tech­nol­o­gy. This expan­sion has led to an increased demand for AI specialists.
• Emerg­ing Tech­nolo­gies: The con­tin­u­ous devel­op­ment of emerg­ing tech­nolo­gies, includ­ing machine learn­ing, nat­ur­al lan­guage pro­cess­ing, and com­put­er vision, has cre­at­ed new oppor­tu­ni­ties for AI pro­fes­sion­als to con­tribute to inno­v­a­tive projects and solutions.
• Data-Dri­ven Deci­sion-Mak­ing: Orga­ni­za­tions increas­ing­ly rec­og­nize the val­ue of data-dri­ven deci­sion-mak­ing, lead­ing to a demand for pro­fes­sion­als who can lever­age AI and machine learn­ing to extract insights from large datasets.
• Automa­tion and Effi­cien­cy: Busi­ness­es are inte­grat­ing AI to enhance effi­cien­cy, auto­mate process­es, and improve over­all oper­a­tions. This trend has fueled the need for pro­fes­sion­als who can design, imple­ment, and main­tain AI systems.
• Star­tups and Estab­lished Com­pa­nies: Both star­tups and estab­lished com­pa­nies are invest­ing in AI tal­ent. Star­tups often focus on dis­rup­tive AI appli­ca­tions, while larg­er cor­po­ra­tions inte­grate AI into their exist­ing infra­struc­ture to stay competitive.
• Cross-Indus­try Adop­tion: AI is not lim­it­ed to the tech sec­tor; it is increas­ing­ly being adopt­ed across diverse indus­tries. This cross-indus­try adop­tion broad­ens the range of oppor­tu­ni­ties for AI pro­fes­sion­als in areas such as health­care, finance, mar­ket­ing, and more.
• Research and Devel­op­ment: The field of AI is dynam­ic, with ongo­ing research and devel­op­ment. Pro­fes­sion­als engaged in AI research con­tribute to advance­ments and are sought after by aca­d­e­m­ic insti­tu­tions, research labs, and tech companies.

Keep in mind, while the demand for AI pro­fes­sion­als is high, the spe­cif­ic job mar­ket can vary depend­ing on fac­tors like geo­graph­ic loca­tion, the indus­try you’re inter­est­ed in, and the spe­cif­ic AI skills you pos­sess. Of course, the job mar­ket is also sub­ject to eco­nom­ic and tech­no­log­i­cal changes.

To get the most accu­rate and up-to-date infor­ma­tion, con­sid­er check­ing job boards, indus­try reports, and rep­utable sources for the lat­est trends in the AI job mar­ket. Net­work­ing with pro­fes­sion­als in the field and stay­ing informed about indus­try devel­op­ments can also pro­vide valu­able insights into cur­rent job mar­ket conditions.

An AI degree can help you learn the basics need­ed to enter this chal­leng­ing field. If you want to build soft­ware or machines that respond to the envi­ron­ment around them, this might be the right field for you. For exam­ple, AI can pro­vide solu­tions that mit­i­gate the impact of client change and pre­dict the path of disease.

Even if you’re just look­ing for job secu­ri­ty, this is one of the most in-demand skill sets you can develop.

What Are the Highest-Paying AI Careers? 

Whether you are a return­ing adult stu­dent or just enter­ing col­lege, you may have the same ques­tion. How do I get into AI and what can I do to suc­ceed in not only the pro­gram but my future career? You can rec­og­nize that AI is like­ly to impact almost every indus­try in the future. There­fore, tak­ing class­es that sup­port your area of exper­tise may be in your best interest.

With a lit­tle expe­ri­ence and the edu­ca­tion you need to suc­ceed, you can eas­i­ly find your­self mak­ing great mon­ey in the future. Here’s a quick look at some of the most lucra­tive AI careers.

Although these salaries are impres­sive, it’s impor­tant to remem­ber that you may hold many oth­er titles. How­ev­er, entry-lev­el salaries are com­pet­i­tive with oth­er indus­tries and exceed the aver­age salary of most wage earners.

Above all, an AI bach­e­lor’s degree gives you the skills that you need to jump­start your career. It’s also a great way to segue from one field to anoth­er. Do your research and choose the right school, com­par­ing their core class­es to ensure they inte­grate your aca­d­e­m­ic and career goals well.

Relat­ed:

Top 10 Bach­e­lor of Com­put­er Sci­ence Degree Programs

20 Best Online Bach­e­lors of Data Sci­ence Programs

15 Best Online Busi­ness Ana­lyt­ics Programs

15 Best Online Engi­neer­ing Degree Bachelor’s Programs